Title: | Summary Scores of the Adolescent Brain Cognitive Development (ABCD) Study |
Description: | Provides functions to compute summary scores (besides proprietary ones) reported in the tabulated data resource that is released by the Adolescent Brain Cognitive Development (ABCD) study. Feldstein Ewing and Luciana (2018) https://www.sciencedirect.com/journal/developmental-cognitive-neuroscience/vol/32. |
URL: | https://software.nbdc-datahub.org/ABCDscores/ |
Version: | 6.0.1 |
Depends: | R (≥ 4.3.0) |
Imports: | chk, cli, dplyr, glue, lubridate, magrittr, purrr, rlang, stringr, tibble, tidyr, stats, utils |
Suggests: | arrow, rmarkdown, roxyglobals, testthat (≥ 3.0.0), knitr, reactable, readr, usethis |
License: | GPL (≥ 3) |
Encoding: | UTF-8 |
RoxygenNote: | 7.3.2 |
Config/testthat/edition: | 3 |
Config/Needs/website: | rmarkdown |
VignetteBuilder: | knitr |
LazyData: | true |
Config/roxyglobals/filename: | globals.R |
Config/roxyglobals/unique: | TRUE |
NeedsCompilation: | no |
Packaged: | 2025-09-08 19:53:56 UTC; lz |
Author: | Janosch Linkersdoerfer
|
Maintainer: | Janosch Linkersdoerfer <dairc.service@gmail.com> |
Repository: | CRAN |
Date/Publication: | 2025-09-11 09:00:16 UTC |
ABCDscores: Summary Scores of the Adolescent Brain Cognitive Development Study
Description
This package provides functions to compute summary scores (besides proprietary ones) reported in the tabulated data resource that is released by the Adolescent Brain Cognitive Development (ABCD) study. Feldstein Ewing and Luciana (2018) https://www.sciencedirect.com/journal/developmental-cognitive-neuroscience/vol/32.
Author(s)
Maintainer: Janosch Linkersdoerfer dairc.service@gmail.com (ORCID)
Authors:
Le Zhang lezhang100@gmail.com (ORCID)
Olivier Celhay olivier.celhay@gmail.com (ORCID)
Biplabendu Das biplabendu.das@gmail.com (ORCID)
Sammy Berman sammyberman@gmail.com (ORCID)
Laura Ziemer lrziemer@gmail.com (ORCID)
See Also
Useful links:
Check arguments for TLFB summary score functions
Description
Validates the arguments to compute a TLFB substance use score.
Usage
check_args_tlfb(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL,
position = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
position |
character. The position of the substance use event. Must be
one of |
Value
NULL
. Invisibly returns NULL
if all checks pass. Otherwise, an
error is raised.
Check an output field and assign NA when input variables all have NAs
Description
Checks the specified output column in a data frame and assigns NA to its value depending on the missingness of a set of input columns.
If allow_missingness = TRUE
, the output column is set to NA only when all the specified input columns are NA.
If allow_missingness = FALSE
, the output column is set to NA when any of the input columns are NA.
This function is useful for propagating missingness from input variables to a derived output.
Usage
check_assign_na(data, output, input, allow_missingness = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
output |
character of length 1. The name of the first variable/column. |
input |
character. The name of the second variable/column. |
allow_missingness |
logical. Default set to TRUE. If TRUE, |
Value
tbl. The input data frame with the output
column modified.
Examples
# Example data
dat <- tibble::tibble(
a = c(1, NA, 3),
b = c(NA, NA, 2),
c = c(1, 2, 3),
out = c(10, 11, 12)
)
# Assign NA to out when all of a and b are NA
check_assign_na(
dat,
output = "out", input = c("a", "b"), allow_missingness = TRUE
)
# Assign NA to out when any of a and b are NA
check_assign_na(
dat,
output = "out", input = c("a", "b"), allow_missingness = FALSE
)
Check if a column name already exists in a data frame
Description
This function checks if a column name already exists in a data frame. If the column name already exists, the function will abort with an error.
Usage
check_col_names(data, names)
Arguments
data |
tbl. Data frame to check for the column name. |
names |
character vector, The name(s) of the column to check for. |
Value
NULL. The function will abort with an error if the column name already exists.
Examples
data <- tibble::tibble(a = NA, b = NA, c = NA)
try({
check_col_names(data, c("a", "b", "c"))
check_col_names(data, c("a", "d"))
})
Combine columns
Description
Combines two columns into one. The name of the first column is used for the new column, the second column is removed. Used for cases where different versions of the same variable exist that have to be combined before computing a summary score.
Usage
combine_cols(data, col_1, col_2, name = NULL, keep_other = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
col_1 |
character. The name of the first variable/column. |
col_2 |
character. The name of the second variable/column. |
name |
character. The name of the field with the combined data.
By default, |
keep_other |
logical. Whether to combine the combined column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the combined column and the second
column removed. The name of the combined column is the same as col_1
,
or user-specified in the name
argument.
Examples
data <- tibble::tibble(
var_id = c("A", "B", "C"),
var_orig = c(1, NA, 3),
var_alt = c(NA, 2, 4)
)
data |>
combine_cols(
col_1 = "var_orig",
col_2 = "var_alt"
)
data |>
combine_cols(
"var_orig",
"var_alt",
name = "out"
)
data |>
combine_cols(
"var_orig",
"var_alt",
name = "out",
keep_other = FALSE
)
Combine levels from two variables to create a new variable
Description
Combines levels from two columns into new level stored into a new column. Allows users to create new classifications using levels defined in existing fields.
Usage
combine_levels(data, vars, conds, default = NA, combine = TRUE)
Arguments
data |
tbl. Data frame containing the two columns to be summarized. |
vars |
named list of length 1. The name of the list component will be used as the name for the newly created variable/column, and the character elements specifies the two existing fields from which the levels will be combined. |
conds |
named list. The name of the each of the list element will be used as the label for the new level created, and the two character vectors represent the levels in the first and second variables, respectively, that will be combined to create the new level. |
default |
character (or |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the new column with combined levels appended at the end.
Examples
data <- tibble::tibble(
var_1 = c("a", "b", "b", "c"),
var_2 = c(1, NA, 2, 3)
)
data |>
combine_levels(
vars = list(
"var_3" = c("var_1", "var_2")
),
conds = list(
"a1" = list("a", 1),
"b0" = list("b", NA),
"b2" = list("b", 2)
),
default = "var_1",
combine = TRUE
)
Compute "Cohort description: Household income - 3 levels"
Description
Computes the summary score ab_g_dyn__cohort_income__hhold__3lvl
Cohort description: Household income - 3 levels
-
Summarized variables:
-
ab_p_demo__income__hhold_001
-
ab_p_demo__income__hhold_001__v01
-
Usage
compute_ab_g_dyn__cohort_income__hhold__3lvl(
data,
name = "ab_g_dyn__cohort_income__hhold__3lvl",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ab_g_dyn__cohort_income__hhold__6lvl()
Compute all the ab_g_dyn scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_ab_g_dyn_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ab_g_dyn_all(data)
## End(Not run)
Compute all the ab_g_stc scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_ab_g_stc_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ab_g_stc_all(data)
## End(Not run)
Compute time interval between two dates
Description
Calculate the time difference between two dates in specified units (years, months, or days). Uses lubridate intervals for accurate calculations across calendar irregularities.
Usage
compute_age(date_start, date_end, unit = c("years", "months", "days"))
Arguments
date_start |
Starting date. Must be a date or datetime object compatible with lubridate. |
date_end |
Ending date. Must be a date or datetime object compatible with lubridate. |
unit |
Character string specifying the unit for the result. Must be one of "years", "months", or "days". Defaults to "years". |
Value
A numeric value representing the time difference in the specified unit.
Examples
# Calculate age in years
compute_age(as.Date("1990-01-01"), as.Date("2024-01-01"))
# Calculate age in months
compute_age(as.Date("2023-01-01"), as.Date("2024-01-01"), unit = "months")
# Calculate age in days
compute_age(as.Date("2023-12-01"), as.Date("2024-01-01"), unit = "days")
Compute "Family Environment Scale [Parent] (Cohesion): Number missing"
Description
Computes the summary score fc_p_fes__cohes_nm
(Family Environment Scale [Parent] (Cohesion): Number missing)
-
Summarized variables:
-
fc_p_fes__cohes_001
-
fc_p_fes__cohes_002
-
fc_p_fes__cohes_003
-
fc_p_fes__cohes_004
-
fc_p_fes__cohes_005
-
fc_p_fes__cohes_006
-
fc_p_fes__cohes_007
-
fc_p_fes__cohes_008
-
fc_p_fes__cohes_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__cohes_nm(data, name = "fc_p_fes__cohes_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_fes__cohes_mean()
Compute "Family Environment Scale [Parent] (Conflict): Number missing"
Description
Computes the summary score fc_p_fes__confl_nm
(Family Environment Scale [Parent] (Conflict): Number missing)
-
Summarized variables:
-
fc_p_fes__confl_001
-
fc_p_fes__confl_002
-
fc_p_fes__confl_003
-
fc_p_fes__confl_004
-
fc_p_fes__confl_005
-
fc_p_fes__confl_006
-
fc_p_fes__confl_007
-
fc_p_fes__confl_008
-
fc_p_fes__confl_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__confl_nm(data, name = "fc_p_fes__confl_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_fes__confl_mean()
Compute "Family Environment Scale [Parent] (Expression): Number missing"
Description
Computes the summary score fc_p_fes__expr_nm
(Family Environment Scale [Parent] (Expression): Number missing)
-
Summarized variables:
-
fc_p_fes__expr_001
-
fc_p_fes__expr_002
-
fc_p_fes__expr_003
-
fc_p_fes__expr_004
-
fc_p_fes__expr_005
-
fc_p_fes__expr_006
-
fc_p_fes__expr_007
-
fc_p_fes__expr_008
-
fc_p_fes__expr_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__expr_nm(data, name = "fc_p_fes__expr_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Family Environment Scale [Parent] (Intellectual and cultural): Number missing"
Description
Computes the summary score fc_p_fes__intelcult_nm
(Family Environment Scale [Parent] (Intellectual and cultural): Number
missing)
-
Summarized variables:
-
fc_p_fes__intelcult_001
-
fc_p_fes__intelcult_002
-
fc_p_fes__intelcult_003
-
fc_p_fes__intelcult_004
-
fc_p_fes__intelcult_005
-
fc_p_fes__intelcult_006
-
fc_p_fes__intelcult_007
-
fc_p_fes__intelcult_008
-
fc_p_fes__intelcult_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__intelcult_nm(
data,
name = "fc_p_fes__intelcult_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_fes__intelcult_mean()
Compute "Family Environment Scale [Parent] (Organization): Number missing"
Description
Computes the summary score fc_p_fes__org_nm
(Family Environment Scale [Parent] (Organization): Number missing)
-
Summarized variables:
-
fc_p_fes__org_001
-
fc_p_fes__org_002
-
fc_p_fes__org_003
-
fc_p_fes__org_004
-
fc_p_fes__org_005
-
fc_p_fes__org_006
-
fc_p_fes__org_007
-
fc_p_fes__org_008
-
fc_p_fes__org_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__org_nm(data, name = "fc_p_fes__org_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Family Environment Scale [Parent] (Activity and recreational): Number missing"
Description
Computes the summary score fc_p_fes__rec_nm
(Family Environment Scale [Parent] (Activity and recreational): Number
missing)
-
Summarized variables:
-
fc_p_fes__rec_001
-
fc_p_fes__rec_002
-
fc_p_fes__rec_003
-
fc_p_fes__rec_004
-
fc_p_fes__rec_005
-
fc_p_fes__rec_006
-
fc_p_fes__rec_007
-
fc_p_fes__rec_008
-
fc_p_fes__rec_009
-
-
Excluded values: none
Usage
compute_fc_p_fes__rec_nm(data, name = "fc_p_fes__rec_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_p_fes summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_fes_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_fes_all(data)
## End(Not run)
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and attachment): Number missing"
Description
Computes the summary score fc_p_meim__commattach_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and
attachment): Number missing)
-
Summarized variables:
-
fc_p_meim__commattach_001
-
fc_p_meim__commattach_002
-
fc_p_meim__commattach_003
-
-
Excluded values: none
Usage
compute_fc_p_meim__commattach_nm(
data,
name = "fc_p_meim__commattach_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_meim__commattach_mean()
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration): Number missing"
Description
Computes the summary score fc_p_meim__explor_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration):
Number missing)
-
Summarized variables:
-
fc_p_meim__explor_001
-
fc_p_meim__explor_002
-
fc_p_meim__explor_003
-
-
Excluded values: none
Usage
compute_fc_p_meim__explor_nm(
data,
name = "fc_p_meim__explor_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_meim__explor_mean()
Compute all the fc_p_meim summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_meim_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_meim_all(data)
## End(Not run)
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent]: Number missing"
Description
Computes the summary score fc_p_meim_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent]: Number missing)
-
Summarized variables:
-
fc_p_meim__commattach_001
-
fc_p_meim__commattach_002
-
fc_p_meim__commattach_003
-
fc_p_meim__explor_001
-
fc_p_meim__explor_002
-
fc_p_meim__explor_003
-
-
Excluded values: none
Usage
compute_fc_p_meim_nm(data, name = "fc_p_meim_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Neighborhood Collective Efficacy [Parent] (Community cohesion): Number missing"
Description
Computes the summary score fc_p_nce__cc_nm
(Neighborhood Collective Efficacy [Parent] (Community cohesion): Number
missing)
-
Summarized variables:
-
fc_p_nce__cc_001
-
fc_p_nce__cc_002
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
fc_p_nce__cc_005
-
-
Excluded values:
777
Usage
compute_fc_p_nce__cc_nm(data, name = "fc_p_nce__cc_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Neighborhood Collective Efficacy [Parent] (Informal social control): Number missing"
Description
Computes the summary score fc_p_nce__isc_nm
(Neighborhood Collective Efficacy [Parent] (Informal social control): Number
missing)
-
Summarized variables:
-
fc_p_nce__isc_001
-
fc_p_nce__isc_002
-
fc_p_nce__isc_003
-
fc_p_nce__isc_004
-
fc_p_nce__isc_005
-
-
Excluded values:
777
Usage
compute_fc_p_nce__isc_nm(data, name = "fc_p_nce__isc_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_p_nce summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_nce_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_nce_all(data)
## End(Not run)
Compute "Neighborhood Collective Efficacy [Parent]: Number missing"
Description
Computes the summary score fc_p_nce_nm
(Neighborhood Collective Efficacy [Parent]: Number missing)
-
Summarized variables:
-
fc_p_nce__cc_001
-
fc_p_nce__cc_002
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
fc_p_nce__cc_005
-
fc_p_nce__isc_001
-
fc_p_nce__isc_002
-
fc_p_nce__isc_003
-
fc_p_nce__isc_004
-
fc_p_nce__isc_005
-
-
Excluded values:
777
Usage
compute_fc_p_nce_nm(data, name = "fc_p_nce_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Neighborhood Safety & Crime [Parent] (Neighborhood safety): Number missing"
Description
Computes the summary score fc_p_nsc__ns_nm
(Neighborhood Safety & Crime [Parent] (Neighborhood safety): Number missing)
-
Summarized variables:
-
fc_p_nsc__ns_001
-
fc_p_nsc__ns_002
-
fc_p_nsc__ns_003
-
-
Excluded values:
777
999
Usage
compute_fc_p_nsc__ns_nm(data, name = "fc_p_nsc__ns_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_p_nsc summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_nsc_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_nsc_all(data)
## End(Not run)
Compute "Parental Knowledge Scale [Parent]: Number missing"
Description
Computes the summary score fc_p_pk__knowl_nm
(Parental Knowledge Scale [Parent]: Number missing)
-
Summarized variables:
-
fc_p_pk__knowl_001
-
fc_p_pk__knowl_002
-
fc_p_pk__knowl_003
-
fc_p_pk__knowl_004
-
fc_p_pk__knowl_005
-
fc_p_pk__knowl_006
-
fc_p_pk__knowl_007
-
fc_p_pk__knowl_008
-
fc_p_pk__knowl_009
-
-
Excluded values:
777
Usage
compute_fc_p_pk__knowl_nm(data, name = "fc_p_pk__knowl_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_p_pk summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_pk_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_pk_all(data)
## End(Not run)
Compute all the fc_p_psb summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_psb_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_psb_all(data)
## End(Not run)
Compute "Prosocial Behavior [Parent]: Number missing"
Description
Computes the summary score fc_p_psb_nm
(Prosocial Behavior [Parent]: Number missing)
-
Summarized variables:
-
fc_p_psb_001
-
fc_p_psb_002
-
fc_p_psb_003
-
-
Excluded values: none
Usage
compute_fc_p_psb_nm(data, name = "fc_p_psb_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Parent] (Independence and self-reliance): Number missing"
Description
Computes the summary score fc_p_vs__indselfrel_nm
(Values Scale [Parent] (Independence and
self-reliance): Number missing)
-
Summarized variables:
-
fc_p_vs__indselfrel_001
-
fc_p_vs__indselfrel_002
-
fc_p_vs__indselfrel_003
-
fc_p_vs__indselfrel_004
-
fc_p_vs__indselfrel_005
-
-
Excluded values: none
Usage
compute_fc_p_vs__indselfrel_nm(
data,
name = "fc_p_vs__indselfrel_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_p_vs__indselfrel_mean()
Compute "Values Scale [Parent] (Family obligation): Number missing"
Description
Computes the summary score fc_p_vs__obl_nm
(Values Scale [Parent] (Family obligation): Number
missing)
-
Summarized variables:
-
fc_p_vs__obl_001
-
fc_p_vs__obl_002
-
fc_p_vs__obl_003
-
fc_p_vs__obl_004
-
fc_p_vs__obl_005
-
-
Excluded values: none
Usage
compute_fc_p_vs__obl_nm(data, name = "fc_p_vs__obl_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Parent] (Family as referent): Number missing"
Description
Computes the summary score fc_p_vs__ref_nm
(Values Scale [Parent] (Family as referent): Number
missing)
-
Summarized variables:
-
fc_p_vs__ref_001
-
fc_p_vs__ref_002
-
fc_p_vs__ref_003
-
fc_p_vs__ref_004
-
fc_p_vs__ref_005
-
-
Excluded values: none
Usage
compute_fc_p_vs__ref_nm(data, name = "fc_p_vs__ref_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Parent] (Religion): Number missing"
Description
Computes the summary score fc_p_vs__relig_nm
(Values Scale [Parent] (Religion): Number missing)
-
Summarized variables:
-
fc_p_vs__relig_001
-
fc_p_vs__relig_002
-
fc_p_vs__relig_003
-
fc_p_vs__relig_004
-
fc_p_vs__relig_005
-
fc_p_vs__relig_006
-
fc_p_vs__relig_007
-
-
Excluded values: none
Usage
compute_fc_p_vs__relig_nm(data, name = "fc_p_vs__relig_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Parent] (Family support): Number missing"
Description
Computes the summary score fc_p_vs__supp_nm
(Values Scale [Parent] (Family support): Number
missing)
-
Summarized variables:
-
fc_p_vs__supp_001
-
fc_p_vs__supp_002
-
fc_p_vs__supp_003
-
fc_p_vs__supp_004
-
fc_p_vs__supp_005
-
fc_p_vs__supp_006
-
-
Excluded values: none
Usage
compute_fc_p_vs__supp_nm(data, name = "fc_p_vs__supp_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_p_vs summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_p_vs_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_p_vs_all(data)
## End(Not run)
Compute "Activity Space [Youth] (Safety): Number missing"
Description
Computes the summary score fc_y_as__safe_nm
(Activity Space [Youth] (Safety): Number missing)
-
Summarized variables:
-
fc_y_as__safe_001a
-
fc_y_as__safe_001b
-
fc_y_as__safe_001c
-
-
Excluded values: none
Usage
compute_fc_y_as__safe_nm(data, name = "fc_y_as__safe_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_as summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_as_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_as_all(data)
## End(Not run)
Compute "Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A): Number missing"
Description
Computes the summary score fc_y_crpbi__cg1_nm
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A):
Number missing)
-
Summarized variables:
-
fc_y_crpbi__cg1_002
-
fc_y_crpbi__cg1_003
-
fc_y_crpbi__cg1_004
-
fc_y_crpbi__cg1_005
-
fc_y_crpbi__cg1_006
-
-
Excluded values: none
Usage
compute_fc_y_crpbi__cg1_nm(data, name = "fc_y_crpbi__cg1_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_crpbi__cg1_mean()
Compute "Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B): Number missing"
Description
Computes the summary score fc_y_crpbi__cg2_nm
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B):
Number missing)
-
Summarized variables:
-
fc_y_crpbi__cg2_002
-
fc_y_crpbi__cg2_003
-
fc_y_crpbi__cg2_004
-
fc_y_crpbi__cg2_005
-
fc_y_crpbi__cg2_006
-
-
Excluded values: none
Usage
compute_fc_y_crpbi__cg2_nm(data, name = "fc_y_crpbi__cg2_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_crpbi__cg2_mean()
Compute all the fc_y_crpbi summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_crpbi_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_crpbi_all(data)
## End(Not run)
Compute "Experiences with Unfair Treatment [Youth] (Ethnicity): Number missing"
Description
Computes the summary score fc_y_eut__ethn_nm
(Experiences with Unfair Treatment [Youth] (Ethnicity): Number missing)
-
Summarized variables:
-
fc_y_eut__ethn_001a
-
fc_y_eut__ethn_001b
-
fc_y_eut__ethn_001c
-
fc_y_eut__ethn_001d
-
fc_y_eut__ethn_002
-
fc_y_eut__ethn_003a
-
fc_y_eut__ethn_003b
-
fc_y_eut__ethn_003c
-
-
Excluded values:
444
777
999
Usage
compute_fc_y_eut__ethn_nm(data, name = "fc_y_eut__ethn_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_eut summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_eut_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_eut_all(data)
## End(Not run)
Compute "Family Environment Scale [Youth] (Cohesion): Number missing"
Description
Computes the summary score fc_y_fes__cohes_nm
(Family Environment Scale [Youth] (Cohesion): Number missing)
-
Summarized variables:
-
fc_y_fes__cohes_001
-
fc_y_fes__cohes_002
-
fc_y_fes__cohes_003
-
fc_y_fes__cohes_004
-
fc_y_fes__cohes_005
-
fc_y_fes__cohes_006
-
fc_y_fes__cohes_007
-
fc_y_fes__cohes_008
-
fc_y_fes__cohes_009
-
-
Excluded values: none
Usage
compute_fc_y_fes__cohes_nm(data, name = "fc_y_fes__cohes_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_fes__cohes_mean()
Compute "Family Environment Scale [Youth] (Conflict): Number missing"
Description
Computes the summary score fc_y_fes__confl_nm
(Family Environment Scale [Youth] (Conflict): Number missing)
-
Summarized variables:
-
fc_y_fes__confl_001
-
fc_y_fes__confl_002
-
fc_y_fes__confl_003
-
fc_y_fes__confl_004
-
fc_y_fes__confl_005
-
fc_y_fes__confl_006
-
fc_y_fes__confl_007
-
fc_y_fes__confl_008
-
fc_y_fes__confl_009
-
-
Excluded values: none
Usage
compute_fc_y_fes__confl_nm(data, name = "fc_y_fes__confl_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_fes__confl_mean()
Compute all the fc_y_fes summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_fes_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_fes_all(data)
## End(Not run)
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and attachment): Number missing"
Description
Computes the summary score fc_y_meim__commattach_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and
attachment): Number missing)
-
Summarized variables:
-
fc_y_meim__commattach_001
-
fc_y_meim__commattach_002
-
fc_y_meim__commattach_003
-
-
Excluded values: none
Usage
compute_fc_y_meim__commattach_nm(
data,
name = "fc_y_meim__commattach_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_meim__commattach_mean()
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration): Number missing"
Description
Computes the summary score fc_y_meim__explor_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration):
Number missing)
-
Summarized variables:
-
fc_y_meim__explor_001
-
fc_y_meim__explor_002
-
fc_y_meim__explor_003
-
-
Excluded values: none
Usage
compute_fc_y_meim__explor_nm(
data,
name = "fc_y_meim__explor_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_meim__explor_mean()
Compute all the fc_y_meim summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_meim_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_meim_all(data)
## End(Not run)
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth]: Number missing"
Description
Computes the summary score fc_y_meim_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth]: Number missing)
-
Summarized variables:
-
fc_y_meim__commattach_001
-
fc_y_meim__commattach_002
-
fc_y_meim__commattach_003
-
fc_y_meim__explor_001
-
fc_y_meim__explor_002
-
fc_y_meim__explor_003
-
-
Excluded values: none
Usage
compute_fc_y_meim_nm(data, name = "fc_y_meim_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Multidimensional Neglectful Behavior Scale [Youth] (Education support): Number missing"
Description
Computes the summary score fc_y_mnbs__edusupp_nm
(Multidimensional Neglectful Behavior Scale [Youth] (Education support):
Number missing)
-
Summarized variables:
-
fc_y_mnbs__edusupp_001
-
fc_y_mnbs__edusupp_002
-
fc_y_mnbs__edusupp_003
-
-
Excluded values:
777
Usage
compute_fc_y_mnbs__edusupp_nm(
data,
name = "fc_y_mnbs__edusupp_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_mnbs__edusupp_mean()
Compute "Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Number missing"
Description
Computes the summary score fc_y_mnbs__superv_nm
(Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Number
missing)
-
Summarized variables:
-
fc_y_mnbs__superv_001
-
fc_y_mnbs__superv_002
-
fc_y_mnbs__superv_003
-
fc_y_mnbs__superv_004
-
fc_y_mnbs__superv_005
-
-
Excluded values:
777
Usage
compute_fc_y_mnbs__superv_nm(
data,
name = "fc_y_mnbs__superv_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_mnbs__superv_mean()
Compute all the fc_y_mnbs summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_mnbs_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_mnbs_all(data)
## End(Not run)
Compute "Multidimensional Neglectful Behavior Scale [Youth]: Number missing"
Description
Computes the summary score fc_y_mnbs_nm
(Multidimensional Neglectful Behavior Scale [Youth]: Number missing)
-
Summarized variables:
-
fc_y_mnbs__edusupp_001
-
fc_y_mnbs__edusupp_002
-
fc_y_mnbs__edusupp_003
-
fc_y_mnbs__superv_001
-
fc_y_mnbs__superv_002
-
fc_y_mnbs__superv_003
-
fc_y_mnbs__superv_004
-
fc_y_mnbs__superv_005
-
-
Excluded values:
777
Usage
compute_fc_y_mnbs_nm(data, name = "fc_y_mnbs_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_pm summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_pm_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_pm_all(data)
## End(Not run)
Compute "Parental Monitoring [Youth]: Number missing"
Description
Computes the summary score fc_y_pm_nm
(Parental Monitoring [Youth]: Number missing)
-
Summarized variables:
-
fc_y_pm_001
-
fc_y_pm_002
-
fc_y_pm_003
-
fc_y_pm_004
-
fc_y_pm_005
-
-
Excluded values:
777
Usage
compute_fc_y_pm_nm(data, name = "fc_y_pm_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_pnh summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_pnh_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_pnh_all(data)
## End(Not run)
Compute "Peer Network Health [Youth]: Number missing"
Description
Computes the summary score fc_y_pnh_nm
(Peer Network Health [Youth]: Number missing)
-
Summarized variables:
-
fc_y_pnh_001
-
fc_y_pnh_002
-
fc_y_pnh_002__01
-
fc_y_pnh_003
-
fc_y_pnh_003__01
-
-
Excluded values: none
Usage
compute_fc_y_pnh_nm(data, name = "fc_y_pnh_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_psb summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_psb_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_psb_all(data)
## End(Not run)
Compute "Prosocial Behavior [Youth]: Number missing"
Description
Computes the summary score fc_y_psb_nm
(Prosocial Behavior [Youth]: Number missing)
-
Summarized variables:
-
fc_y_psb_001
-
fc_y_psb_002
-
fc_y_psb_003
-
-
Excluded values: none
Usage
compute_fc_y_psb_nm(data, name = "fc_y_psb_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_rpi summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_rpi_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_rpi_all(data)
## End(Not run)
Compute "Resistance to Peer Influence [Youth]: Number missing"
Description
Computes the summary score fc_y_rpi_nm
(Resistance to Peer Influence [Youth]: Number missing)
-
Summarized variables:
-
fc_y_rpi_001
-
fc_y_rpi_002
-
fc_y_rpi_003
-
fc_y_rpi_004
-
fc_y_rpi_005
-
fc_y_rpi_006
-
fc_y_rpi_007
-
fc_y_rpi_008
-
fc_y_rpi_009
-
fc_y_rpi_010
-
-
Excluded values: none
Usage
compute_fc_y_rpi_nm(data, name = "fc_y_rpi_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "School Risk & Protective Factors [Youth] (School disengagement): Number missing"
Description
Computes the summary score fc_y_srpf__dis_nm
(School Risk & Protective Factors [Youth] (School disengagement): Number
missing)
-
Summarized variables:
-
fc_y_srpf__dis_001
-
fc_y_srpf__dis_002
-
-
Excluded values: none
Usage
compute_fc_y_srpf__dis_nm(data, name = "fc_y_srpf__dis_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "School Risk & Protective Factors [Youth] (School environment): Number missing"
Description
Computes the summary score fc_y_srpf__env_nm
(School Risk & Protective Factors [Youth] (School environment): Number
missing)
-
Summarized variables:
-
fc_y_srpf__env_001
-
fc_y_srpf__env_002
-
fc_y_srpf__env_003
-
fc_y_srpf__env_004
-
fc_y_srpf__env_005
-
fc_y_srpf__env_006
-
-
Excluded values: none
Usage
compute_fc_y_srpf__env_nm(data, name = "fc_y_srpf__env_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "School Risk & Protective Factors [Youth] (School involvement): Number missing"
Description
Computes the summary score fc_y_srpf__involv_nm
(School Risk & Protective Factors [Youth] (School involvement): Number
missing)
-
Summarized variables:
-
fc_y_srpf__involv_001
-
fc_y_srpf__involv_002
-
fc_y_srpf__involv_003
-
fc_y_srpf__involv_004
-
-
Excluded values: none
Usage
compute_fc_y_srpf__involv_nm(
data,
name = "fc_y_srpf__involv_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_srpf__involv_mean()
Compute all the fc_y_srpf summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_srpf_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_srpf_all(data)
## End(Not run)
Compute "Values Scale [Youth] (Independence and self-reliance): Number missing"
Description
Computes the summary score fc_y_vs__indselfrel_nm
(Values Scale [Youth] (Independence and
self-reliance): Number missing)
-
Summarized variables:
-
fc_y_vs__indselfrel_001
-
fc_y_vs__indselfrel_002
-
fc_y_vs__indselfrel_003
-
fc_y_vs__indselfrel_004
-
fc_y_vs__indselfrel_005
-
-
Excluded values: none
Usage
compute_fc_y_vs__indselfrel_nm(
data,
name = "fc_y_vs__indselfrel_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_fc_y_vs__indselfrel_mean()
Compute "Values Scale [Youth] (Family obligation): Number missing"
Description
Computes the summary score fc_y_vs__obl_nm
(Values Scale [Youth] (Family obligation): Number
missing)
-
Summarized variables:
-
fc_y_vs__obl_001
-
fc_y_vs__obl_002
-
fc_y_vs__obl_003
-
fc_y_vs__obl_004
-
fc_y_vs__obl_005
-
-
Excluded values: none
Usage
compute_fc_y_vs__obl_nm(data, name = "fc_y_vs__obl_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Youth] (Family as referent): Number missing"
Description
Computes the summary score fc_y_vs__ref_nm
(Values Scale [Youth] (Family as referent): Number
missing)
-
Summarized variables:
-
fc_y_vs__ref_001
-
fc_y_vs__ref_002
-
fc_y_vs__ref_003
-
fc_y_vs__ref_004
-
fc_y_vs__ref_005
-
-
Excluded values: none
Usage
compute_fc_y_vs__ref_nm(data, name = "fc_y_vs__ref_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Youth] (Religion): Number missing"
Description
Computes the summary score fc_y_vs__relig_nm
(Values Scale [Youth] (Religion): Number missing)
-
Summarized variables:
-
fc_y_vs__relig_001
-
fc_y_vs__relig_002
-
fc_y_vs__relig_003
-
fc_y_vs__relig_004
-
fc_y_vs__relig_005
-
fc_y_vs__relig_006
-
fc_y_vs__relig_007
-
-
Excluded values: none
Usage
compute_fc_y_vs__relig_nm(data, name = "fc_y_vs__relig_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Values Scale [Youth] (Family support): Number missing"
Description
Computes the summary score fc_y_vs__supp_nm
(Values Scale [Youth] (Family support): Number
missing)
-
Summarized variables:
-
fc_y_vs__supp_001
-
fc_y_vs__supp_002
-
fc_y_vs__supp_003
-
fc_y_vs__supp_004
-
fc_y_vs__supp_005
-
fc_y_vs__supp_006
-
-
Excluded values: none
Usage
compute_fc_y_vs__supp_nm(data, name = "fc_y_vs__supp_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the fc_y_vs summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_vs_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_vs_all(data)
## End(Not run)
Compute all the fc_y_wpss summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_fc_y_wpss_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_fc_y_wpss_all(data)
## End(Not run)
Compute "Wills Problem Solving Scale [Youth]: Number missing"
Description
Computes the summary score fc_y_wpss_nm
(Wills Problem Solving Scale [Youth]: Number missing)
-
Summarized variables:
-
fc_y_wpss_001
-
fc_y_wpss_002
-
fc_y_wpss_003
-
fc_y_wpss_004
-
fc_y_wpss_005
-
fc_y_wpss_006
-
-
Excluded values: none
Usage
compute_fc_y_wpss_nm(data, name = "fc_y_wpss_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Adult Behavior Checklist [Parent] (Adaptive Functioning Scale - Friends): Sum"
Description
Computes the summary score mh_p_abcl__afs__frnd_sum
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): Sum
-
Summarized variables:
-
mh_p_abcl__frnd_001
-
mh_p_abcl__frnd_002
-
mh_p_abcl__frnd_003
-
mh_p_abcl__frnd_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_mh_p_abcl__afs__frnd_sum(
data,
name = "mh_p_abcl__afs__frnd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__afs__frnd_nm()
Examples
## Not run:
compute_mh_p_abcl__afs__frnd_sum(data) |>
select(
any_of(c("mh_p_abcl__afs__frnd_sum", vars_mh_p_abcl__afs__frnd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Adaptive Functioning Scale - Friends): T-score"
Description
Computes the summary score mh_p_abcl__afs__frnd_tscore
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): T-score
-
Summarized variables:
-
mh_p_abcl__frnd_001
-
mh_p_abcl__frnd_002
-
mh_p_abcl__frnd_003
-
mh_p_abcl__frnd_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_mh_p_abcl__afs__frnd_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__afs__frnd_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__afs__frnd_nm()
Examples
## Not run:
compute_mh_p_abcl__afs__frnd_tscore(data) |>
select(
any_of(c("mh_p_abcl__afs__frnd_tscore", vars_mh_p_abcl__afs__frnd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Critical items): Sum"
Description
Computes the summary score mh_p_abcl__critic_sum
Adult Behavior Checklist [Parent] (Critical items): Sum
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 19 items missing
Usage
compute_mh_p_abcl__critic_sum(
data,
name = "mh_p_abcl__critic_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__critic_nm()
Examples
## Not run:
compute_mh_p_abcl__critic_sum(data) |>
select(
any_of(c("mh_p_abcl__critic_sum", vars_mh_p_abcl__critic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Critical items): T-score"
Description
Computes the summary score mh_p_abcl__critic_tscore
Adult Behavior Checklist [Parent] (Critical items): T-score
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 19 items missing
Usage
compute_mh_p_abcl__critic_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__critic_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__critic_nm()
Examples
## Not run:
compute_mh_p_abcl__critic_tscore(data) |>
select(
any_of(c("mh_p_abcl__critic_tscore", vars_mh_p_abcl__critic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum"
Description
Computes the summary score mh_p_abcl__dsm__adhd_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum
-
Summarized variables:
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_abcl__dsm__adhd_sum(
data,
name = "mh_p_abcl__dsm__adhd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__adhd_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__adhd_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__adhd_sum", vars_mh_p_abcl__dsm__adhd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): T-score"
Description
Computes the summary score mh_p_abcl__dsm__adhd_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
T-score
-
Summarized variables:
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_abcl__dsm__adhd_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__adhd_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__adhd_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__adhd_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__adhd_tscore", vars_mh_p_abcl__dsm__adhd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial personality problems): Sum"
Description
Computes the summary score mh_p_abcl__dsm__antsoc_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Sum
-
Summarized variables:
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 20 items missing
Usage
compute_mh_p_abcl__dsm__antsoc_sum(
data,
name = "mh_p_abcl__dsm__antsoc_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__antsoc_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__antsoc_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__antsoc_sum", vars_mh_p_abcl__dsm__antsoc))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial personality problems): T-score"
Description
Computes the summary score mh_p_abcl__dsm__antsoc_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): T-score
-
Summarized variables:
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 20 items missing
Usage
compute_mh_p_abcl__dsm__antsoc_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__antsoc_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__antsoc_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__antsoc_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__antsoc_tscore", vars_mh_p_abcl__dsm__antsoc))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety problems): Sum"
Description
Computes the summary score mh_p_abcl__dsm__anx_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): Sum
-
Summarized variables:
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_abcl__dsm__anx_sum(
data,
name = "mh_p_abcl__dsm__anx_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__anx_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__anx_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__anx_sum", vars_mh_p_abcl__dsm__anx))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety problems): T-score"
Description
Computes the summary score mh_p_abcl__dsm__anx_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): T-score
-
Summarized variables:
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_abcl__dsm__anx_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__anx_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__anx_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__anx_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__anx_tscore", vars_mh_p_abcl__dsm__anx))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant personality problems): Sum"
Description
Computes the summary score mh_p_abcl__dsm__avoid_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Sum
-
Summarized variables:
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_abcl__dsm__avoid_sum(
data,
name = "mh_p_abcl__dsm__avoid_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__avoid_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__avoid_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__avoid_sum", vars_mh_p_abcl__dsm__avoid))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant personality problems): T-score"
Description
Computes the summary score mh_p_abcl__dsm__avoid_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): T-score
-
Summarized variables:
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_abcl__dsm__avoid_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__avoid_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__avoid_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__avoid_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__avoid_tscore", vars_mh_p_abcl__dsm__avoid))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): Sum"
Description
Computes the summary score mh_p_abcl__dsm__dep_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Sum
-
Summarized variables:
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_abcl__dsm__dep_sum(
data,
name = "mh_p_abcl__dsm__dep_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__dep_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__dep_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__dep_sum", vars_mh_p_abcl__dsm__dep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): T-score"
Description
Computes the summary score mh_p_abcl__dsm__dep_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): T-score
-
Summarized variables:
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_abcl__dsm__dep_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__dep_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__dep_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__dep_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__dep_tscore", vars_mh_p_abcl__dsm__dep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_abcl__dsm__somat_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
-
Summarized variables:
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_abcl__dsm__somat_sum(
data,
name = "mh_p_abcl__dsm__somat_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__somat_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__somat_sum(data) |>
select(
any_of(c("mh_p_abcl__dsm__somat_sum", vars_mh_p_abcl__dsm__somat))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_p_abcl__dsm__somat_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): T-score
-
Summarized variables:
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_abcl__dsm__somat_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__dsm__somat_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__dsm__somat_nm()
Examples
## Not run:
compute_mh_p_abcl__dsm__somat_tscore(data) |>
select(
any_of(c("mh_p_abcl__dsm__somat_tscore", vars_mh_p_abcl__dsm__somat))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days drug use): Sum"
Description
Computes the summary score mh_p_abcl__su__drg_sum
Adult Behavior Checklist [Parent] (Days drug use): Sum
-
Summarized variables:
-
mh_p_abcl__drg_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__drg_sum(
data,
name = "mh_p_abcl__su__drg_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__drg_nm()
Examples
## Not run:
compute_mh_p_abcl__su__drg_sum(data) |>
select(
any_of(c("mh_p_abcl__su__drg_sum", vars_mh_p_abcl__su__drg))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days drug use): T-score"
Description
Computes the summary score mh_p_abcl__su__drg_tscore
Adult Behavior Checklist [Parent] (Days drug use): T-score
-
Summarized variables:
-
mh_p_abcl__drg_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__drg_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__su__drg_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__drg_nm()
Examples
## Not run:
compute_mh_p_abcl__su__drg_tscore(data) |>
select(
any_of(c("mh_p_abcl__su__drg_tscore", vars_mh_p_abcl__su__drg))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days Drunk): Sum"
Description
Computes the summary score mh_p_abcl__su__drunk_sum
Adult Behavior Checklist [Parent] (Days Drunk): Sum
-
Summarized variables:
-
mh_p_abcl__drunk_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__drunk_sum(
data,
name = "mh_p_abcl__su__drunk_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__drunk_nm()
Examples
## Not run:
compute_mh_p_abcl__su__drunk_sum(data) |>
select(
any_of(c("mh_p_abcl__su__drunk_sum", vars_mh_p_abcl__su__drunk))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days Drunk): T-score"
Description
Computes the summary score mh_p_abcl__su__drunk_tscore
Adult Behavior Checklist [Parent] (Days Drunk): T-score
-
Summarized variables:
-
mh_p_abcl__drunk_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__drunk_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__su__drunk_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__drunk_nm()
Examples
## Not run:
compute_mh_p_abcl__su__drunk_tscore(data) |>
select(
any_of(c("mh_p_abcl__su__drunk_tscore", vars_mh_p_abcl__su__drunk))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Tobacco per day): Sum"
Description
Computes the summary score mh_p_abcl__su__nic_sum
Adult Behavior Checklist [Parent] (Tobacco per day): Sum
-
Summarized variables:
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__nic_sum(
data,
name = "mh_p_abcl__su__nic_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__nic_nm()
Examples
## Not run:
compute_mh_p_abcl__su__nic_sum(data) |>
select(
any_of(c("mh_p_abcl__su__nic_sum", vars_mh_p_abcl__su__nic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Tobacco per day): T-score"
Description
Computes the summary score mh_p_abcl__su__nic_tscore
Adult Behavior Checklist [Parent] (Tobacco per day): T-score
-
Summarized variables:
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 items missing
Usage
compute_mh_p_abcl__su__nic_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__su__nic_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__su__nic_nm()
Examples
## Not run:
compute_mh_p_abcl__su__nic_tscore(data) |>
select(
any_of(c("mh_p_abcl__su__nic_tscore", vars_mh_p_abcl__su__nic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Substance use): Sum"
Description
Computes the summary score mh_p_abcl__su_sum
Adult Behavior Checklist [Parent] (Substance use): Sum
-
Summarized variables:
-
mh_p_abcl__drg_001
-
mh_p_abcl__drunk_001
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 3 items missing
Usage
compute_mh_p_abcl__su_sum(
data,
name = "mh_p_abcl__su_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_abcl__su_sum(data) |>
select(
any_of(c("mh_p_abcl__su_sum", vars_mh_p_abcl__su))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Substance use): T-score"
Description
Computes the summary score mh_p_abcl__su_tscore
Adult Behavior Checklist [Parent] (Substance use): T-score
-
Summarized variables:
-
mh_p_abcl__drg_001
-
mh_p_abcl__drunk_001
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 3 items missing
Usage
compute_mh_p_abcl__su_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__su_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_abcl__su_tscore(data) |>
select(
any_of(c("mh_p_abcl__su_tscore", vars_mh_p_abcl__su))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): Sum"
Description
Computes the summary score mh_p_abcl__synd__aggr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Sum
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 16 items missing
Usage
compute_mh_p_abcl__synd__aggr_sum(
data,
name = "mh_p_abcl__synd__aggr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__aggr_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__aggr_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__aggr_sum", vars_mh_p_abcl__synd__aggr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): T-score"
Description
Computes the summary score mh_p_abcl__synd__aggr_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): T-score
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 16 items missing
Usage
compute_mh_p_abcl__synd__aggr_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__aggr_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__aggr_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__aggr_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__aggr_tscore", vars_mh_p_abcl__synd__aggr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): Sum"
Description
Computes the summary score mh_p_abcl__synd__anxdep_sum
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Sum
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_abcl__synd__anxdep_sum(
data,
name = "mh_p_abcl__synd__anxdep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__anxdep_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__anxdep_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__anxdep_sum", vars_mh_p_abcl__synd__anxdep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): T-score"
Description
Computes the summary score mh_p_abcl__synd__anxdep_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): T-score
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_abcl__synd__anxdep_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__anxdep_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__anxdep_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__anxdep_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__anxdep_tscore", vars_mh_p_abcl__synd__anxdep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Attention problems): Sum"
Description
Computes the summary score mh_p_abcl__synd__attn_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Sum
-
Summarized variables:
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_abcl__synd__attn_sum(
data,
name = "mh_p_abcl__synd__attn_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__attn_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__attn_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__attn_sum", vars_mh_p_abcl__synd__attn))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Attention problems): T-score"
Description
Computes the summary score mh_p_abcl__synd__attn_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): T-score
-
Summarized variables:
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_abcl__synd__attn_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__attn_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__attn_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__attn_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__attn_tscore", vars_mh_p_abcl__synd__attn))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - External): Sum"
Description
Computes the summary score mh_p_abcl__synd__ext_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - External): Sum
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 35 items missing
Usage
compute_mh_p_abcl__synd__ext_sum(
data,
name = "mh_p_abcl__synd__ext_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__ext_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__ext_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__ext_sum", vars_mh_p_abcl__synd__ext))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - External): T-score"
Description
Computes the summary score mh_p_abcl__synd__ext_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - External): T-score
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 35 items missing
Usage
compute_mh_p_abcl__synd__ext_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__ext_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__ext_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__ext_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__ext_tscore", vars_mh_p_abcl__synd__ext))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing): Sum"
Description
Computes the summary score mh_p_abcl__synd__int_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Sum
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_p_abcl__synd__int_sum(
data,
name = "mh_p_abcl__synd__int_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__int_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__int_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__int_sum", vars_mh_p_abcl__synd__int))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing): T-score"
Description
Computes the summary score mh_p_abcl__synd__int_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
T-score
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_p_abcl__synd__int_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__int_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__int_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__int_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__int_tscore", vars_mh_p_abcl__synd__int))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Sum"
Description
Computes the summary score mh_p_abcl__synd__intru_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Sum
-
Summarized variables:
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_abcl__synd__intru_sum(
data,
name = "mh_p_abcl__synd__intru_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__intru_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__intru_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__intru_sum", vars_mh_p_abcl__synd__intru))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): T-score"
Description
Computes the summary score mh_p_abcl__synd__intru_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive):
T-score
-
Summarized variables:
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_abcl__synd__intru_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__intru_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__intru_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__intru_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__intru_tscore", vars_mh_p_abcl__synd__intru))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems): Sum"
Description
Computes the summary score mh_p_abcl__synd__othpr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Sum
-
Summarized variables:
-
mh_p_abcl__othpr_001
-
mh_p_abcl__othpr_002
-
mh_p_abcl__othpr_003
-
mh_p_abcl__othpr_004
-
mh_p_abcl__othpr_005
-
mh_p_abcl__othpr_006
-
mh_p_abcl__othpr_007
-
mh_p_abcl__othpr_008
-
mh_p_abcl__othpr_009
-
mh_p_abcl__othpr_010
-
mh_p_abcl__othpr_011
-
mh_p_abcl__othpr_012
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 25 items missing
Usage
compute_mh_p_abcl__synd__othpr_sum(
data,
name = "mh_p_abcl__synd__othpr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__othpr_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__othpr_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__othpr_sum", vars_mh_p_abcl__synd__othpr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): Sum"
Description
Computes the summary score mh_p_abcl__synd__rule_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Sum
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_abcl__synd__rule_sum(
data,
name = "mh_p_abcl__synd__rule_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__rule_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__rule_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__rule_sum", vars_mh_p_abcl__synd__rule))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): T-score"
Description
Computes the summary score mh_p_abcl__synd__rule_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): T-score
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_abcl__synd__rule_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__rule_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__rule_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__rule_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__rule_tscore", vars_mh_p_abcl__synd__rule))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_abcl__synd__som_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Sum
-
Summarized variables:
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__som_sum(
data,
name = "mh_p_abcl__synd__som_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__som_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__som_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__som_sum", vars_mh_p_abcl__synd__som))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_p_abcl__synd__som_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): T-score
-
Summarized variables:
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__som_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__som_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__som_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__som_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__som_tscore", vars_mh_p_abcl__synd__som))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems): Sum"
Description
Computes the summary score mh_p_abcl__synd__tho_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Sum
-
Summarized variables:
-
mh_p_abcl__tho_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_006
-
mh_p_abcl__tho_007
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__tho_sum(
data,
name = "mh_p_abcl__synd__tho_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__tho_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__tho_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__tho_sum", vars_mh_p_abcl__synd__tho))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems): T-score"
Description
Computes the summary score mh_p_abcl__synd__tho_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
T-score
-
Summarized variables:
-
mh_p_abcl__tho_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_006
-
mh_p_abcl__tho_007
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__tho_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__tho_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__tho_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__tho_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__tho_tscore", vars_mh_p_abcl__synd__tho))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Sum"
Description
Computes the summary score mh_p_abcl__synd__wthdr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Sum
-
Summarized variables:
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__wthdr_sum(
data,
name = "mh_p_abcl__synd__wthdr_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__wthdr_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__wthdr_sum(data) |>
select(
any_of(c("mh_p_abcl__synd__wthdr_sum", vars_mh_p_abcl__synd__wthdr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): T-score"
Description
Computes the summary score mh_p_abcl__synd__wthdr_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn):
T-score
-
Summarized variables:
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_abcl__synd__wthdr_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl__synd__wthdr_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_abcl__synd__wthdr_nm()
Examples
## Not run:
compute_mh_p_abcl__synd__wthdr_tscore(data) |>
select(
any_of(c("mh_p_abcl__synd__wthdr_tscore", vars_mh_p_abcl__synd__wthdr))
)
## End(Not run)
Compute all summary scores for mh_p_abcl.
Description
This function computes all summary scores for the mh_p_abcl form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_abcl_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_abcl_all(data)
## End(Not run)
Compute "Adult Behavior Checklist [Parent]: Sum"
Description
Computes the summary score mh_p_abcl_sum
Adult Behavior Checklist [Parent]: Sum
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__rule_003
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__som_001
-
mh_p_abcl__othpr_001
-
mh_p_abcl__othpr_002
-
mh_p_abcl__othpr_003
-
mh_p_abcl__othpr_004
-
mh_p_abcl__othpr_005
-
mh_p_abcl__othpr_006
-
mh_p_abcl__othpr_007
-
mh_p_abcl__othpr_008
-
mh_p_abcl__othpr_009
-
mh_p_abcl__othpr_010
-
mh_p_abcl__othpr_011
-
mh_p_abcl__othpr_012
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 8 of 118 items missing
Usage
compute_mh_p_abcl_sum(
data,
name = "mh_p_abcl_sum",
max_na = 8,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_abcl_sum(data) |>
select(
any_of(c("mh_p_abcl_sum", vars_mh_p_abcl))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent]: T-score"
Description
Computes the summary score mh_p_abcl_tscore
Adult Behavior Checklist [Parent]: T-score
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__rule_003
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__som_001
-
mh_p_abcl__othpr_001
-
mh_p_abcl__othpr_002
-
mh_p_abcl__othpr_003
-
mh_p_abcl__othpr_004
-
mh_p_abcl__othpr_005
-
mh_p_abcl__othpr_006
-
mh_p_abcl__othpr_007
-
mh_p_abcl__othpr_008
-
mh_p_abcl__othpr_009
-
mh_p_abcl__othpr_010
-
mh_p_abcl__othpr_011
-
mh_p_abcl__othpr_012
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 8 of 118 items missing
Usage
compute_mh_p_abcl_tscore(
data,
data_norm = NULL,
name = "mh_p_abcl_tscore",
col_age = "mh_p_abcl__cg2__age_001",
col_sex = "mh_p_abcl__cg2_sex",
max_na = 8,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_abcl_tscore(data) |>
select(
any_of(c("mh_p_abcl_tscore", vars_mh_p_abcl))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Adaptive Functioning Scale - Personal strength): Sum"
Description
Computes the summary score mh_p_asr__afs__strng_sum
Adult Self Report [Parent] (Adaptive Functioning Scale - Personal
strength): Sum
-
Summarized variables:
-
mh_p_asr__strng_001
-
mh_p_asr__strng_002
-
mh_p_asr__strng_003
-
mh_p_asr__strng_004
-
mh_p_asr__strng_005
-
mh_p_asr__strng_006
-
mh_p_asr__strng_007
-
mh_p_asr__strng_008
-
mh_p_asr__strng_009
-
mh_p_asr__strng_010
-
mh_p_asr__strng_011
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_p_asr__afs__strng_sum(
data,
name = "mh_p_asr__afs__strng_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__afs__strng_nm()
Examples
## Not run:
compute_mh_p_asr__afs__strng_sum(data) |>
select(
any_of(c("mh_p_asr__afs__strng_sum", vars_mh_p_asr__afs__strng))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Critical Items): Sum"
Description
Computes the summary score mh_p_asr__critic_sum
Adult Self Report [Parent] (Critical Items): Sum
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__rule_001
-
mh_p_asr__rule_003
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 19 items missing
Usage
compute_mh_p_asr__critic_sum(
data,
name = "mh_p_asr__critic_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_asr__critic_sum(data) |>
select(
any_of(c("mh_p_asr__critic_sum", vars_mh_p_asr__critic))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Hyperactivity-Impulsivity): Sum"
Description
Computes the summary score mh_p_asr__dsm__adhd__hypimp_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD
Hyperactivity-Impulsivity): Sum
-
Summarized variables:
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_asr__dsm__adhd__hypimp_sum(
data,
name = "mh_p_asr__dsm__adhd__hypimp_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__adhd__hypimp_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__adhd__hypimp_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd__hypimp_sum", vars_mh_p_asr__dsm__adhd__hypimp))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention): Sum"
Description
Computes the summary score mh_p_asr__dsm__adhd__inatt_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention):
Sum
-
Summarized variables:
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_asr__dsm__adhd__inatt_sum(
data,
name = "mh_p_asr__dsm__adhd__inatt_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__adhd__inatt_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__adhd__inatt_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd__inatt_sum", vars_mh_p_asr__dsm__adhd__inatt))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Sum"
Description
Computes the summary score mh_p_asr__dsm__adhd_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Sum
-
Summarized variables:
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_asr__dsm__adhd_sum(
data,
name = "mh_p_asr__dsm__adhd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__adhd_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__adhd_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd_sum", vars_mh_p_asr__dsm__adhd))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial personality problems): Sum"
Description
Computes the summary score mh_p_asr__dsm__antsoc_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Sum
-
Summarized variables:
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 20 items missing
Usage
compute_mh_p_asr__dsm__antsoc_sum(
data,
name = "mh_p_asr__dsm__antsoc_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__antsoc_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__antsoc_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__antsoc_sum", vars_mh_p_asr__dsm__antsoc))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems): Sum"
Description
Computes the summary score mh_p_asr__dsm__anx_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems):
Sum
-
Summarized variables:
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_asr__dsm__anx_sum(
data,
name = "mh_p_asr__dsm__anx_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__anx_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__anx_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__anx_sum", vars_mh_p_asr__dsm__anx))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant personality problems): Sum"
Description
Computes the summary score mh_p_asr__dsm__avoid_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Sum
-
Summarized variables:
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_asr__dsm__avoid_sum(
data,
name = "mh_p_asr__dsm__avoid_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__avoid_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__avoid_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__avoid_sum", vars_mh_p_asr__dsm__avoid))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive problems): Sum"
Description
Computes the summary score mh_p_asr__dsm__dep_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive
problems): Sum
-
Summarized variables:
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__tho__dep_001
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_asr__dsm__dep_sum(
data,
name = "mh_p_asr__dsm__dep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__dep_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__dep_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__dep_sum", vars_mh_p_asr__dsm__dep))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_asr__dsm__somat_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
-
Summarized variables:
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_asr__dsm__somat_sum(
data,
name = "mh_p_asr__dsm__somat_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__dsm__somat_nm()
Examples
## Not run:
compute_mh_p_asr__dsm__somat_sum(data) |>
select(
any_of(c("mh_p_asr__dsm__somat_sum", vars_mh_p_asr__dsm__somat))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior): Sum"
Description
Computes the summary score mh_p_asr__synd__aggr_sum
Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior): Sum
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_asr__synd__aggr_sum(
data,
name = "mh_p_asr__synd__aggr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__aggr_nm()
Examples
## Not run:
compute_mh_p_asr__synd__aggr_sum(data) |>
select(
any_of(c("mh_p_asr__synd__aggr_sum", vars_mh_p_asr__synd__aggr))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed): Sum"
Description
Computes the summary score mh_p_asr__synd__anxdep_sum
Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed): Sum
-
Summarized variables:
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 18 items missing
Usage
compute_mh_p_asr__synd__anxdep_sum(
data,
name = "mh_p_asr__synd__anxdep_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__anxdep_nm()
Examples
## Not run:
compute_mh_p_asr__synd__anxdep_sum(data) |>
select(
any_of(c("mh_p_asr__synd__anxdep_sum", vars_mh_p_asr__synd__anxdep))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Attention problems): Sum"
Description
Computes the summary score mh_p_asr__synd__attn_sum
Adult Self Report [Parent] (Syndrome Scale - Attention problems): Sum
-
Summarized variables:
-
mh_p_asr__attn_001
-
mh_p_asr__attn_002
-
mh_p_asr__attn_003
-
mh_p_asr__attn_004
-
mh_p_asr__attn_005
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_asr__synd__attn_sum(
data,
name = "mh_p_asr__synd__attn_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__attn_nm()
Examples
## Not run:
compute_mh_p_asr__synd__attn_sum(data) |>
select(
any_of(c("mh_p_asr__synd__attn_sum", vars_mh_p_asr__synd__attn))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Externalizing): Sum"
Description
Computes the summary score mh_p_asr__synd__ext_sum
Adult Self Report [Parent] (Syndrome Scale - Externalizing): Sum
-
Summarized variables:
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
mh_p_asr__rule_001
-
mh_p_asr__rule_002
-
mh_p_asr__rule_003
-
mh_p_asr__rule_004
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 35 items missing
Usage
compute_mh_p_asr__synd__ext_sum(
data,
name = "mh_p_asr__synd__ext_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__ext_nm()
Examples
## Not run:
compute_mh_p_asr__synd__ext_sum(data) |>
select(
any_of(c("mh_p_asr__synd__ext_sum", vars_mh_p_asr__synd__ext))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Internalizing): Sum"
Description
Computes the summary score mh_p_asr__synd__int_sum
Adult Self Report [Parent] (Syndrome Scale - Internalizing): Sum
-
Summarized variables:
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__som_001
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 39 items missing
Usage
compute_mh_p_asr__synd__int_sum(
data,
name = "mh_p_asr__synd__int_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__int_nm()
Examples
## Not run:
compute_mh_p_asr__synd__int_sum(data) |>
select(
any_of(c("mh_p_asr__synd__int_sum", vars_mh_p_asr__synd__int))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Intrusive): Sum"
Description
Computes the summary score mh_p_asr__synd__intru_sum
Adult Self Report [Parent] (Syndrome Scale - Intrusive): Sum
-
Summarized variables:
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_p_asr__synd__intru_sum(
data,
name = "mh_p_asr__synd__intru_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__intru_nm()
Examples
## Not run:
compute_mh_p_asr__synd__intru_sum(data) |>
select(
any_of(c("mh_p_asr__synd__intru_sum", vars_mh_p_asr__synd__intru))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Other problems): Sum"
Description
Computes the summary score mh_p_asr__synd__othpr_sum
Adult Self Report [Parent] (Syndrome Scale - Other problems): Sum
-
Summarized variables:
-
mh_p_asr__othpr_001
-
mh_p_asr__othpr_002
-
mh_p_asr__othpr_003
-
mh_p_asr__othpr_004
-
mh_p_asr__othpr_005
-
mh_p_asr__othpr_006
-
mh_p_asr__othpr_007
-
mh_p_asr__othpr_008
-
mh_p_asr__othpr_009
-
mh_p_asr__othpr_010
-
mh_p_asr__othpr_011
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 21 items missing
Usage
compute_mh_p_asr__synd__othpr_sum(
data,
name = "mh_p_asr__synd__othpr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__othpr_nm()
Examples
## Not run:
compute_mh_p_asr__synd__othpr_sum(data) |>
select(
any_of(c("mh_p_asr__synd__othpr_sum", vars_mh_p_asr__synd__othpr))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior): Sum"
Description
Computes the summary score mh_p_asr__synd__rule_sum
Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior):
Sum
-
Summarized variables:
-
mh_p_asr__rule_001
-
mh_p_asr__rule_002
-
mh_p_asr__rule_003
-
mh_p_asr__rule_004
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_asr__synd__rule_sum(
data,
name = "mh_p_asr__synd__rule_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__rule_nm()
Examples
## Not run:
compute_mh_p_asr__synd__rule_sum(data) |>
select(
any_of(c("mh_p_asr__synd__rule_sum", vars_mh_p_asr__synd__rule))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_asr__synd__som_sum
Adult Self Report [Parent] (Syndrome Scale - Somatic complaints): Sum
-
Summarized variables:
-
mh_p_asr__som_001
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 12 items missing
Usage
compute_mh_p_asr__synd__som_sum(
data,
name = "mh_p_asr__synd__som_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__som_nm()
Examples
## Not run:
compute_mh_p_asr__synd__som_sum(data) |>
select(
any_of(c("mh_p_asr__synd__som_sum", vars_mh_p_asr__synd__som))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Thought problems): Sum"
Description
Computes the summary score mh_p_asr__synd__tho_sum
Adult Self Report [Parent] (Syndrome Scale - Thought problems): Sum
-
Summarized variables:
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_003
-
mh_p_asr__tho_004
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho_008
-
mh_p_asr__tho__hypimp_001
-
mh_p_asr__tho__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_p_asr__synd__tho_sum(
data,
name = "mh_p_asr__synd__tho_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__tho_nm()
Examples
## Not run:
compute_mh_p_asr__synd__tho_sum(data) |>
select(
any_of(c("mh_p_asr__synd__tho_sum", vars_mh_p_asr__synd__tho))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Sum"
Description
Computes the summary score mh_p_asr__synd__wthdr_sum
Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Sum
-
Summarized variables:
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_asr__synd__wthdr_sum(
data,
name = "mh_p_asr__synd__wthdr_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_asr__synd__wthdr_nm()
Examples
## Not run:
compute_mh_p_asr__synd__wthdr_sum(data) |>
select(
any_of(c("mh_p_asr__synd__wthdr_sum", vars_mh_p_asr__synd__wthdr))
)
## End(Not run)
Compute all summary scores for mh_p_asr.
Description
This function computes all summary scores for the mh_p_asr form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_asr_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_asr_all(data)
## End(Not run)
Compute "Adult Self Report [Parent]: Sum"
Description
Computes the summary score mh_p_asr_sum
Adult Self Report [Parent]: Sum
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__rule_001
-
mh_p_asr__rule_003
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho__dep_001
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__wthdr__dep_001
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__attn_001
-
mh_p_asr__attn_002
-
mh_p_asr__attn_003
-
mh_p_asr__attn_004
-
mh_p_asr__attn_005
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
mh_p_asr__rule_002
-
mh_p_asr__rule_004
-
mh_p_asr__som_001
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__othpr_001
-
mh_p_asr__othpr_002
-
mh_p_asr__othpr_003
-
mh_p_asr__othpr_004
-
mh_p_asr__othpr_005
-
mh_p_asr__othpr_006
-
mh_p_asr__othpr_007
-
mh_p_asr__othpr_008
-
mh_p_asr__othpr_009
-
mh_p_asr__othpr_010
-
mh_p_asr__othpr_011
-
mh_p_asr__tho_003
-
mh_p_asr__tho_004
-
mh_p_asr__tho_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 8 of 120 items missing
Usage
compute_mh_p_asr_sum(
data,
name = "mh_p_asr_sum",
max_na = 8,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_asr_sum(data) |>
select(
any_of(c("mh_p_asr_sum", vars_mh_p_asr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__adhd_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_cbcl__dsm__adhd_sum(
data,
name = "mh_p_cbcl__dsm__adhd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__adhd_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__adhd_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__adhd_sum", vars_mh_p_cbcl__dsm__adhd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__adhd_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
T-score
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_cbcl__dsm__adhd_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__adhd_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__adhd_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__adhd_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__adhd_tscore", vars_mh_p_cbcl__dsm__adhd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__anx_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
Sum
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_cbcl__dsm__anx_sum(
data,
name = "mh_p_cbcl__dsm__anx_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__anx_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__anx_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__anx_sum", vars_mh_p_cbcl__dsm__anx))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__anx_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
T-score
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_p_cbcl__dsm__anx_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__anx_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__anx_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__anx_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__anx_tscore", vars_mh_p_cbcl__dsm__anx))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct problems): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__cond_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): Sum
-
Summarized variables:
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_cbcl__dsm__cond_sum(
data,
name = "mh_p_cbcl__dsm__cond_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__cond_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__cond_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__cond_sum", vars_mh_p_cbcl__dsm__cond))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct problems): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__cond_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): T-score
-
Summarized variables:
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_cbcl__dsm__cond_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__cond_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__cond_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__cond_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__cond_tscore", vars_mh_p_cbcl__dsm__cond))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__dep_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Sum
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_cbcl__dsm__dep_sum(
data,
name = "mh_p_cbcl__dsm__dep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__dep_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__dep_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__dep_sum", vars_mh_p_cbcl__dsm__dep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__dep_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): T-score
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_cbcl__dsm__dep_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__dep_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__dep_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__dep_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__dep_tscore", vars_mh_p_cbcl__dsm__dep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional Defiant problems): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__opp_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): Sum
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 5 items missing
Usage
compute_mh_p_cbcl__dsm__opp_sum(
data,
name = "mh_p_cbcl__dsm__opp_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__opp_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__opp_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__opp_sum", vars_mh_p_cbcl__dsm__opp))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional Defiant problems): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__opp_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): T-score
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 5 items missing
Usage
compute_mh_p_cbcl__dsm__opp_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__opp_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__opp_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__opp_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__opp_tscore", vars_mh_p_cbcl__dsm__opp))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_cbcl__dsm__somat_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
-
Summarized variables:
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_cbcl__dsm__somat_sum(
data,
name = "mh_p_cbcl__dsm__somat_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__somat_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__somat_sum(data) |>
select(
any_of(c("mh_p_cbcl__dsm__somat_sum", vars_mh_p_cbcl__dsm__somat))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_p_cbcl__dsm__somat_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): T-score
-
Summarized variables:
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_p_cbcl__dsm__somat_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__dsm__somat_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__dsm__somat_nm()
Examples
## Not run:
compute_mh_p_cbcl__dsm__somat_tscore(data) |>
select(
any_of(c("mh_p_cbcl__dsm__somat_tscore", vars_mh_p_cbcl__dsm__somat))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems): Sum"
Description
Computes the summary score mh_p_cbcl__ocd_sum
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems): Sum
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_p_cbcl__ocd_sum(
data,
name = "mh_p_cbcl__ocd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__ocd_sum(data) |>
select(
any_of(c("mh_p_cbcl__ocd_sum", vars_mh_p_cbcl__ocd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems): T-score"
Description
Computes the summary score mh_p_cbcl__ocd_tscore
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems):
T-score
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_p_cbcl__ocd_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__ocd_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__ocd_tscore(data) |>
select(
any_of(c("mh_p_cbcl__ocd_tscore", vars_mh_p_cbcl__ocd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Sum"
Description
Computes the summary score mh_p_cbcl__sct_sum
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Sum
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_mh_p_cbcl__sct_sum(
data,
name = "mh_p_cbcl__sct_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__sct_sum(data) |>
select(
any_of(c("mh_p_cbcl__sct_sum", vars_mh_p_cbcl__sct))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): T-score"
Description
Computes the summary score mh_p_cbcl__sct_tscore
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): T-score
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_mh_p_cbcl__sct_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__sct_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__sct_tscore(data) |>
select(
any_of(c("mh_p_cbcl__sct_tscore", vars_mh_p_cbcl__sct))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Stress): Sum"
Description
Computes the summary score mh_p_cbcl__strs_sum
Child Behavior Checklist [Parent] (Stress): Sum
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_cbcl__strs_sum(
data,
name = "mh_p_cbcl__strs_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__strs_sum(data) |>
select(
any_of(c("mh_p_cbcl__strs_sum", vars_mh_p_cbcl__strs))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Stress): T-score"
Description
Computes the summary score mh_p_cbcl__strs_tscore
Child Behavior Checklist [Parent] (Stress): T-score
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_p_cbcl__strs_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__strs_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl__strs_tscore(data) |>
select(
any_of(c("mh_p_cbcl__strs_tscore", vars_mh_p_cbcl__strs))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): Sum"
Description
Computes the summary score mh_p_cbcl__synd__aggr_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Sum
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 18 items missing
Usage
compute_mh_p_cbcl__synd__aggr_sum(
data,
name = "mh_p_cbcl__synd__aggr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__aggr_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__aggr_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__aggr_sum", vars_mh_p_cbcl__synd__aggr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): T-score"
Description
Computes the summary score mh_p_cbcl__synd__aggr_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): T-score
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 18 items missing
Usage
compute_mh_p_cbcl__synd__aggr_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__aggr_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__aggr_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__aggr_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__aggr_tscore", vars_mh_p_cbcl__synd__aggr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): Sum"
Description
Computes the summary score mh_p_cbcl__synd__anxdep_sum
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Sum
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_cbcl__synd__anxdep_sum(
data,
name = "mh_p_cbcl__synd__anxdep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__anxdep_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__anxdep_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__anxdep_sum", vars_mh_p_cbcl__synd__anxdep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): T-score"
Description
Computes the summary score mh_p_cbcl__synd__anxdep_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): T-score
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_p_cbcl__synd__anxdep_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__anxdep_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__anxdep_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__anxdep_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__anxdep_tscore", vars_mh_p_cbcl__synd__anxdep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Attention problems): Sum"
Description
Computes the summary score mh_p_cbcl__synd__attn_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Sum
-
Summarized variables:
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_p_cbcl__synd__attn_sum(
data,
name = "mh_p_cbcl__synd__attn_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__attn_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__attn_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__attn_sum", vars_mh_p_cbcl__synd__attn))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Attention problems): T-score"
Description
Computes the summary score mh_p_cbcl__synd__attn_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): T-score
-
Summarized variables:
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_p_cbcl__synd__attn_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__attn_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__attn_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__attn_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__attn_tscore", vars_mh_p_cbcl__synd__attn))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing): Sum"
Description
Computes the summary score mh_p_cbcl__synd__ext_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
Sum
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 35 items missing
Usage
compute_mh_p_cbcl__synd__ext_sum(
data,
name = "mh_p_cbcl__synd__ext_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__ext_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__ext_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__ext_sum", vars_mh_p_cbcl__synd__ext))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing): T-score"
Description
Computes the summary score mh_p_cbcl__synd__ext_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
T-score
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 35 items missing
Usage
compute_mh_p_cbcl__synd__ext_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__ext_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__ext_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__ext_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__ext_tscore", vars_mh_p_cbcl__synd__ext))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing): Sum"
Description
Computes the summary score mh_p_cbcl__synd__int_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Sum
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_p_cbcl__synd__int_sum(
data,
name = "mh_p_cbcl__synd__int_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__int_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__int_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__int_sum", vars_mh_p_cbcl__synd__int))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing): T-score"
Description
Computes the summary score mh_p_cbcl__synd__int_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
T-score
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_p_cbcl__synd__int_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__int_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__int_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__int_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__int_tscore", vars_mh_p_cbcl__synd__int))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Other problems): Sum"
Description
Computes the summary score mh_p_cbcl__synd__othpr_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Sum
-
Summarized variables:
-
mh_p_cbcl__othpr_001
-
mh_p_cbcl__othpr_002
-
mh_p_cbcl__othpr_009
-
mh_p_cbcl__othpr_010
-
mh_p_cbcl__othpr_011
-
mh_p_cbcl__othpr_012
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__othpr_003
-
mh_p_cbcl__othpr_004
-
mh_p_cbcl__othpr_005
-
mh_p_cbcl__othpr_006
-
mh_p_cbcl__othpr_007
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__othpr__adhd_001
-
mh_p_cbcl__othpr_008
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 16 items missing
Usage
compute_mh_p_cbcl__synd__othpr_sum(
data,
name = "mh_p_cbcl__synd__othpr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__othpr_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__othpr_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__othpr_sum", vars_mh_p_cbcl__synd__othpr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): Sum"
Description
Computes the summary score mh_p_cbcl__synd__rule_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Sum
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_cbcl__synd__rule_sum(
data,
name = "mh_p_cbcl__synd__rule_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__rule_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__rule_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__rule_sum", vars_mh_p_cbcl__synd__rule))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): T-score"
Description
Computes the summary score mh_p_cbcl__synd__rule_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): T-score
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_p_cbcl__synd__rule_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__rule_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__rule_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__rule_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__rule_tscore", vars_mh_p_cbcl__synd__rule))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale -Social): Sum"
Description
Computes the summary score mh_p_cbcl__synd__soc_sum
Child Behavior Checklist [Parent] (Syndrome Scale -Social): Sum
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_p_cbcl__synd__soc_sum(
data,
name = "mh_p_cbcl__synd__soc_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__soc_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__soc_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__soc_sum", vars_mh_p_cbcl__synd__soc))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale -Social): T-score"
Description
Computes the summary score mh_p_cbcl__synd__soc_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -Social): T-score
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_p_cbcl__synd__soc_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__soc_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__soc_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__soc_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__soc_tscore", vars_mh_p_cbcl__synd__soc))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_p_cbcl__synd__som_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Sum
-
Summarized variables:
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_p_cbcl__synd__som_sum(
data,
name = "mh_p_cbcl__synd__som_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__som_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__som_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__som_sum", vars_mh_p_cbcl__synd__som))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_p_cbcl__synd__som_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): T-score
-
Summarized variables:
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_p_cbcl__synd__som_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__som_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__som_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__som_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__som_tscore", vars_mh_p_cbcl__synd__som))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems): Sum"
Description
Computes the summary score mh_p_cbcl__synd__tho_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Sum
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_cbcl__synd__tho_sum(
data,
name = "mh_p_cbcl__synd__tho_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__tho_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__tho_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__tho_sum", vars_mh_p_cbcl__synd__tho))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems): T-score"
Description
Computes the summary score mh_p_cbcl__synd__tho_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
T-score
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_p_cbcl__synd__tho_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__tho_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__tho_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__tho_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__tho_tscore", vars_mh_p_cbcl__synd__tho))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Withdrawn/Depressed): Sum"
Description
Computes the summary score mh_p_cbcl__synd__wthdep_sum
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): Sum
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_p_cbcl__synd__wthdep_sum(
data,
name = "mh_p_cbcl__synd__wthdep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__wthdep_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__wthdep_sum(data) |>
select(
any_of(c("mh_p_cbcl__synd__wthdep_sum", vars_mh_p_cbcl__synd__wthdep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Withdrawn/Depressed): T-score"
Description
Computes the summary score mh_p_cbcl__synd__wthdep_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): T-score
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_p_cbcl__synd__wthdep_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl__synd__wthdep_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_cbcl__synd__wthdep_nm()
Examples
## Not run:
compute_mh_p_cbcl__synd__wthdep_tscore(data) |>
select(
any_of(c("mh_p_cbcl__synd__wthdep_tscore", vars_mh_p_cbcl__synd__wthdep))
)
## End(Not run)
Compute all summary scores for mh_p_cbcl.
Description
This function computes all summary scores for the mh_p_cbcl form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_cbcl_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_cbcl_all(data)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale): Sum"
Description
Computes the summary score mh_p_cbcl_sum
Child Behavior Checklist [Parent] (Syndrome Scale): Sum
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__othpr_001
-
mh_p_cbcl__othpr_002
-
mh_p_cbcl__othpr_009
-
mh_p_cbcl__othpr_010
-
mh_p_cbcl__othpr_011
-
mh_p_cbcl__othpr_012
-
mh_p_cbcl__othpr_003
-
mh_p_cbcl__othpr_004
-
mh_p_cbcl__othpr_005
-
mh_p_cbcl__othpr_006
-
mh_p_cbcl__othpr_007
-
mh_p_cbcl__othpr_008
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
-
Validation criterion: maximally 8 of 119 items missing
Usage
compute_mh_p_cbcl_sum(
data,
name = "mh_p_cbcl_sum",
max_na = 8,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl_sum(data) |>
select(
any_of(c("mh_p_cbcl_sum", vars_mh_p_cbcl))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale): T-score"
Description
Computes the summary score mh_p_cbcl_tscore
Child Behavior Checklist [Parent] (Syndrome Scale): T-score
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__othpr_001
-
mh_p_cbcl__othpr_002
-
mh_p_cbcl__othpr_009
-
mh_p_cbcl__othpr_010
-
mh_p_cbcl__othpr_011
-
mh_p_cbcl__othpr_012
-
mh_p_cbcl__othpr_003
-
mh_p_cbcl__othpr_004
-
mh_p_cbcl__othpr_005
-
mh_p_cbcl__othpr_006
-
mh_p_cbcl__othpr_007
-
mh_p_cbcl__othpr_008
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
-
Validation criterion: maximally 8 of 119 items missing
Usage
compute_mh_p_cbcl_tscore(
data,
data_norm = NULL,
name = "mh_p_cbcl_tscore",
col_age = "mh_p_cbcl_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 8,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_cbcl_tscore(data) |>
select(
any_of(c("mh_p_cbcl_tscore", vars_mh_p_cbcl))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Attuned): Number missing"
Description
Computes the summary score mh_p_ders__attun_nm
Difficulties in Emotion Regulation Scale [Parent] (Attuned): Number
missing
-
Summarized variables:
-
mh_p_ders__attun_001
-
mh_p_ders__attun_002
-
mh_p_ders__attun_003
-
mh_p_ders__attun_004
-
mh_p_ders__attun_005
-
mh_p_ders__attun_006
-
-
Excluded values:
999
777
Usage
compute_mh_p_ders__attun_nm(
data,
name = "mh_p_ders__attun_nm",
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_ders__attun_mean()
Examples
## Not run:
compute_mh_p_ders__attun_nm(data) |>
select(
any_of(c("mh_p_ders__attun_nm", vars_mh_p_ders__attun))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Catastrophize): Number missing"
Description
Computes the summary score mh_p_ders__catast_nm
Difficulties in Emotion Regulation Scale [Parent] (Catastrophize):
Number missing
-
Summarized variables:
-
mh_p_ders__catast_001
-
mh_p_ders__catast_002
-
mh_p_ders__catast_003
-
mh_p_ders__catast_004
-
mh_p_ders__catast_005
-
mh_p_ders__catast_006
-
mh_p_ders__catast_007
-
mh_p_ders__catast_008
-
mh_p_ders__catast_009
-
mh_p_ders__catast_010
-
mh_p_ders__catast_011
-
mh_p_ders__catast_012
-
-
Excluded values:
999
777
Usage
compute_mh_p_ders__catast_nm(
data,
name = "mh_p_ders__catast_nm",
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_ders__catast_mean()
Examples
## Not run:
compute_mh_p_ders__catast_nm(data) |>
select(
any_of(c("mh_p_ders__catast_nm", vars_mh_p_ders__catast))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Distracted): Number missing"
Description
Computes the summary score mh_p_ders__distract_nm
Difficulties in Emotion Regulation Scale [Parent] (Distracted): Number
missing
-
Summarized variables:
-
mh_p_ders__distract_001
-
mh_p_ders__distract_002
-
mh_p_ders__distract_003
-
mh_p_ders__distract_004
-
-
Excluded values:
999
777
Usage
compute_mh_p_ders__distract_nm(
data,
name = "mh_p_ders__distract_nm",
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_ders__distract_mean()
Examples
## Not run:
compute_mh_p_ders__distract_nm(data) |>
select(
any_of(c("mh_p_ders__distract_nm", vars_mh_p_ders__distract))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Negative Secondary): Number missing"
Description
Computes the summary score mh_p_ders__negscnd_nm
Difficulties in Emotion Regulation Scale [Parent] (Negative
Secondary): Number missing
-
Summarized variables:
-
mh_p_ders__negscnd_001
-
mh_p_ders__negscnd_002
-
mh_p_ders__negscnd_003
-
mh_p_ders__negscnd_004
-
mh_p_ders__negscnd_005
-
mh_p_ders__negscnd_006
-
mh_p_ders__negscnd_007
-
-
Excluded values:
999
777
Usage
compute_mh_p_ders__negscnd_nm(
data,
name = "mh_p_ders__negscnd_nm",
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_p_ders__negscnd_mean()
Examples
## Not run:
compute_mh_p_ders__negscnd_nm(data) |>
select(
any_of(c("mh_p_ders__negscnd_nm", vars_mh_p_ders__negscnd))
)
## End(Not run)
Compute all summary scores for mh_p_ders.
Description
This function computes all summary scores for the mh_p_ders table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_ders_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_ders_all(data)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Activation): Number missing"
Description
Computes the summary score mh_p_eatq__actv_nm
Early Adolescent Temperament Questionnaire [Parent] (Activation):
Number missing
-
Summarized variables:
-
mh_p_eatq__actv_001
-
mh_p_eatq__actv_002
-
mh_p_eatq__actv_003
-
mh_p_eatq__actv_004
-
mh_p_eatq__actv_005
-
mh_p_eatq__actv_006
-
mh_p_eatq__actv_007
-
-
Excluded values: none
Usage
compute_mh_p_eatq__actv_nm(data, name = "mh_p_eatq__actv_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__actv_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__actv_nm(data)
select(
data,
any_of(c("mh_p_eatq__actv_nm", vars_mh_p_eatq__actv))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Affiliation): Number missing"
Description
Computes the summary score mh_p_eatq__affl_nm
Early Adolescent Temperament Questionnaire [Parent] (Affiliation):
Number missing
-
Summarized variables:
-
mh_p_eatq__affl_001
-
mh_p_eatq__affl_002
-
mh_p_eatq__affl_003
-
mh_p_eatq__affl_004
-
mh_p_eatq__affl_005
-
mh_p_eatq__affl_006
-
-
Excluded values: none
Usage
compute_mh_p_eatq__affl_nm(data, name = "mh_p_eatq__affl_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__affl_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__affl_nm(data)
select(
data,
any_of(c("mh_p_eatq__affl_nm", vars_mh_p_eatq__affl))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Aggression): Number missing"
Description
Computes the summary score mh_p_eatq__aggr_nm
Early Adolescent Temperament Questionnaire [Parent] (Aggression):
Number missing
-
Summarized variables:
-
mh_p_eatq__aggr_001
-
mh_p_eatq__aggr_002
-
mh_p_eatq__aggr_003
-
mh_p_eatq__aggr_004
-
mh_p_eatq__aggr_005
-
mh_p_eatq__aggr_006
-
mh_p_eatq__aggr_007
-
-
Excluded values: none
Usage
compute_mh_p_eatq__aggr_nm(data, name = "mh_p_eatq__aggr_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__aggr_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__aggr_nm(data)
select(
data,
any_of(c("mh_p_eatq__aggr_nm", vars_mh_p_eatq__aggr))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Attention): Number missing"
Description
Computes the summary score mh_p_eatq__attn_nm
Early Adolescent Temperament Questionnaire [Parent] (Attention):
Number missing
-
Summarized variables:
-
mh_p_eatq__attn_001
-
mh_p_eatq__attn_002
-
mh_p_eatq__attn_003
-
mh_p_eatq__attn_004
-
mh_p_eatq__attn_005
-
mh_p_eatq__attn_006
-
-
Excluded values: none
Usage
compute_mh_p_eatq__attn_nm(data, name = "mh_p_eatq__attn_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__attn_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__attn_nm(data)
select(
data,
any_of(c("mh_p_eatq__attn_nm", vars_mh_p_eatq__attn))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood): Number missing"
Description
Computes the summary score mh_p_eatq__depm_nm
Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood):
Number missing
-
Summarized variables:
-
mh_p_eatq__depm_001
-
mh_p_eatq__depm_002
-
mh_p_eatq__depm_003
-
mh_p_eatq__depm_004
-
mh_p_eatq__depm_005
-
-
Excluded values: none
Usage
compute_mh_p_eatq__depm_nm(data, name = "mh_p_eatq__depm_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__depm_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__depm_nm(data)
select(
data,
any_of(c("mh_p_eatq__depm_nm", vars_mh_p_eatq__depm))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Fear): Number missing"
Description
Computes the summary score mh_p_eatq__fear_nm
Early Adolescent Temperament Questionnaire [Parent] (Fear): Number
missing
-
Summarized variables:
-
mh_p_eatq__fear_001
-
mh_p_eatq__fear_002
-
mh_p_eatq__fear_003
-
mh_p_eatq__fear_004
-
mh_p_eatq__fear_005
-
mh_p_eatq__fear_006
-
-
Excluded values: none
Usage
compute_mh_p_eatq__fear_nm(data, name = "mh_p_eatq__fear_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__fear_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__fear_nm(data)
select(
data,
any_of(c("mh_p_eatq__fear_nm", vars_mh_p_eatq__fear))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Frustration): Number missing"
Description
Computes the summary score mh_p_eatq__frust_nm
Early Adolescent Temperament Questionnaire [Parent] (Frustration):
Number missing
-
Summarized variables:
-
mh_p_eatq__frust_001
-
mh_p_eatq__frust_002
-
mh_p_eatq__frust_003
-
mh_p_eatq__frust_004
-
mh_p_eatq__frust_005
-
mh_p_eatq__frust_006
-
-
Excluded values: none
Usage
compute_mh_p_eatq__frust_nm(data, name = "mh_p_eatq__frust_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__frust_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__frust_nm(data)
select(
data,
any_of(c("mh_p_eatq__frust_nm", vars_mh_p_eatq__frust))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Inhibition): Number missing"
Description
Computes the summary score mh_p_eatq__inhib_nm
Early Adolescent Temperament Questionnaire [Parent] (Inhibition):
Number missing
-
Summarized variables:
-
mh_p_eatq__inhib_001
-
mh_p_eatq__inhib_002
-
mh_p_eatq__inhib_003
-
mh_p_eatq__inhib_004
-
mh_p_eatq__inhib_005
-
-
Excluded values: none
Usage
compute_mh_p_eatq__inhib_nm(data, name = "mh_p_eatq__inhib_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__inhib_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__inhib_nm(data)
select(
data,
any_of(c("mh_p_eatq__inhib_nm", vars_mh_p_eatq__inhib))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Shyness): Number missing"
Description
Computes the summary score mh_p_eatq__shy_nm
Early Adolescent Temperament Questionnaire [Parent] (Shyness): Number
missing
-
Summarized variables:
-
mh_p_eatq__shy_001
-
mh_p_eatq__shy_002
-
mh_p_eatq__shy_003
-
mh_p_eatq__shy_004
-
mh_p_eatq__shy_005
-
-
Excluded values: none
Usage
compute_mh_p_eatq__shy_nm(data, name = "mh_p_eatq__shy_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
data <- compute_mh_p_eatq__shy_nm(data)
select(
data,
any_of(c("mh_p_eatq__shy_nm", vars_mh_p_eatq__shy))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Effortful control: Combines attention, inhibition, and activation scales): Mean"
Description
Computes the summary score mh_p_eatq__ss__efcon_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Effortful control: Combines attention, inhibition, and activation scales):
Mean
-
Summarized variables:
-
mh_p_eatq__attn_mean
-
mh_p_eatq__inhib_mean
-
mh_p_eatq__actv_mean
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__efcon_mean(
data,
name = "mh_p_eatq__ss__efcon_mean",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Details
Effortful Control = Attention, Inhibitory Control, Activation Control
In the super scale calculation, no NA is allowed.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_mh_p_eatq__ss__efcon_mean(data) |>
select(
any_of(c(
"mh_p_eatq__ss__efcon_mean",
))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Effortful control: Combines attention, inhibition, and activation scales): Number missing"
Description
Computes the summary score mh_p_eatq__ss__efcon_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Effortful control: Combines attention, inhibition, and activation scales):
Number missing
-
Summarized variables:
-
mh_p_eatq__attn_001
-
mh_p_eatq__attn_002
-
mh_p_eatq__attn_003
-
mh_p_eatq__attn_004
-
mh_p_eatq__attn_005
-
mh_p_eatq__attn_006
-
mh_p_eatq__inhib_001
-
mh_p_eatq__inhib_002
-
mh_p_eatq__inhib_003
-
mh_p_eatq__inhib_004
-
mh_p_eatq__inhib_005
-
mh_p_eatq__actv_001
-
mh_p_eatq__actv_002
-
mh_p_eatq__actv_003
-
mh_p_eatq__actv_004
-
mh_p_eatq__actv_005
-
mh_p_eatq__actv_006
-
mh_p_eatq__actv_007
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__efcon_nm(
data,
name = "mh_p_eatq__ss__efcon_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__ss__efcon_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__ss__efcon_nm(data)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Negative Affect: Combines frustration, depressed mood, and aggression scales): Mean"
Description
Computes the summary score mh_p_eatq__ss__negaff_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Negative Affect: Combines frustration, depressed mood, and aggression
scales): Mean
-
Summarized variables:
-
mh_p_eatq__frust_mean
-
mh_p_eatq__depm_mean
-
mh_p_eatq__aggr_mean
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__negaff_mean(
data,
name = "mh_p_eatq__ss__negaff_mean",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Details
Negative Affect = Frustration, Depressive Mood, Aggression
In the super scale calculation, no NA is allowed.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data |>
compute_mh_p_eatq__ss__negaff_mean() |>
select(
any_of(c(
"mh_p_eatq__ss__negaff_mean"
))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Negative Affect: Combines frustration, depressed mood, and aggression scales): Number missing"
Description
Computes the summary score mh_p_eatq__ss__negaff_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Negative Affect: Combines frustration, depressed mood, and aggression
scales): Number missing
-
Summarized variables:
-
mh_p_eatq__frust_001
-
mh_p_eatq__frust_002
-
mh_p_eatq__frust_003
-
mh_p_eatq__frust_004
-
mh_p_eatq__frust_005
-
mh_p_eatq__frust_006
-
mh_p_eatq__depm_001
-
mh_p_eatq__depm_002
-
mh_p_eatq__depm_003
-
mh_p_eatq__depm_004
-
mh_p_eatq__depm_005
-
mh_p_eatq__aggr_001
-
mh_p_eatq__aggr_002
-
mh_p_eatq__aggr_003
-
mh_p_eatq__aggr_004
-
mh_p_eatq__aggr_005
-
mh_p_eatq__aggr_006
-
mh_p_eatq__aggr_007
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__negaff_nm(
data,
name = "mh_p_eatq__ss__negaff_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__ss__negaff_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__ss__negaff_nm(data)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Surgency: Combines surgency, fear (reverse coded), and shyness (reverse coded) scales): Mean [Validation: No more than 0 missing or declined]"
Description
Computes the summary score mh_p_eatq__ss__surg_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Surgency: Combines surgency, fear (reverse coded), and shyness (reverse
coded) scales): Mean [Validation: No more than 0 missing or declined]
-
Summarized variables:
-
mh_p_eatq__surg_mean
-
mh_p_eatq__fear_mean
(revert) -
mh_p_eatq__shy_mean
(revert)
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__surg_mean(
data,
name = "mh_p_eatq__ss__surg_mean",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Details
Surgency = Surgency, Fear (reverse scored), Shyness (reverse scored)
In the super scale calculation, no NA is allowed.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_mh_p_eatq__ss__surg_mean(data) |>
select(
any_of(c(
"mh_p_eatq__ss__surg_mean"
))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Super scale - Surgency: Combines surgency, fear (reverse coded), and shyness (reverse coded) scales): Number missing"
Description
Computes the summary score mh_p_eatq__ss__surg_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Surgency: Combines surgency, fear (reverse coded), and shyness (reverse
coded) scales): Number missing
-
Summarized variables:
-
mh_p_eatq__surg_001
-
mh_p_eatq__surg_002
-
mh_p_eatq__surg_003
-
mh_p_eatq__surg_004
-
mh_p_eatq__surg_005
-
mh_p_eatq__surg_006
-
mh_p_eatq__surg_007
-
mh_p_eatq__surg_008
-
mh_p_eatq__surg_009
-
mh_p_eatq__fear_001
-
mh_p_eatq__fear_002
-
mh_p_eatq__fear_003
-
mh_p_eatq__fear_004
-
mh_p_eatq__fear_005
-
mh_p_eatq__fear_006
-
mh_p_eatq__shy_001
-
mh_p_eatq__shy_002
-
mh_p_eatq__shy_003
-
mh_p_eatq__shy_004
-
mh_p_eatq__shy_005
-
-
Excluded values: none
Usage
compute_mh_p_eatq__ss__surg_nm(
data,
name = "mh_p_eatq__ss__surg_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__ss__surg_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__ss__surg_nm(data)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Surgency): Number missing"
Description
Computes the summary score mh_p_eatq__surg_nm
Early Adolescent Temperament Questionnaire [Parent] (Surgency): Number
missing
-
Summarized variables:
-
mh_p_eatq__surg_001
-
mh_p_eatq__surg_002
-
mh_p_eatq__surg_003
-
mh_p_eatq__surg_004
-
mh_p_eatq__surg_005
-
mh_p_eatq__surg_006
-
mh_p_eatq__surg_007
-
mh_p_eatq__surg_008
-
mh_p_eatq__surg_009
-
-
Excluded values: none
Usage
compute_mh_p_eatq__surg_nm(data, name = "mh_p_eatq__surg_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_p_eatq__surg_mean()
Examples
## Not run:
data <- compute_mh_p_eatq__surg_nm(data)
select(
data,
any_of(c("mh_p_eatq__surg_nm", vars_mh_p_eatq__surg))
)
## End(Not run)
Compute all the EATQ variables
Description
This super function computes all scores in EATQ using all the default arguments.
Usage
compute_mh_p_eatq_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Details
Make sure the data
is the full set of all variables from MCTQ.
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_eatq_all(data)
## End(Not run)
Compute all summary scores for mh_p_gbi.
Description
This function computes all summary scores for the mh_p_gbi table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_gbi_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_gbi_all(data)
## End(Not run)
Compute "Parent General Behavior Inventory [Parent]: Sum"
Description
Computes the summary score mh_p_gbi_sum
Parent General Behavior Inventory [Parent]: Sum
-
Summarized variables:
-
mh_p_gbi_001
-
mh_p_gbi_002
-
mh_p_gbi_003
-
mh_p_gbi_004
-
mh_p_gbi_005
-
mh_p_gbi_006
-
mh_p_gbi_007
-
mh_p_gbi_008
-
mh_p_gbi_009
-
mh_p_gbi_010
-
-
Excluded values: none
-
Validation criterion: none of 10 items missing
Usage
compute_mh_p_gbi_sum(
data,
name = "mh_p_gbi_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_gbi_sum(data) |>
select(
any_of(c("mh_p_gbi_sum", vars_mh_p_gbi))
)
## End(Not run)
Compute "Life Events [Parent] (Experience Bad Events): Count [Validation: No more than 5 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__bad_count
Life Events [Parent] (Experience Bad Events): Count [Validation: No
more than 5 events missing and no experience items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__exp__bad_count(
data,
name = "mh_p_ple__exp__bad_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Bad Events): Count - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__bad_count__v01
Life Events [Parent] (Experience Bad Events): Count - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__exp__bad_count__v01(
data,
name = "mh_p_ple__exp__bad_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Bad Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__bad_count__v02
Life Events [Parent] (Experience Bad Events): Count - Version 2 (Year
4 and Year 5) [Validation: No more than 6 events missing and no experience
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__exp__bad_count__v02(
data,
name = "mh_p_ple__exp__bad_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Bad Events): Count - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__bad_count__v03
Life Events [Parent] (Experience Bad Events): Count - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__exp__bad_count__v03(
data,
name = "mh_p_ple__exp__bad_count__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Bad Events): Count - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__bad_count__v04
Life Events [Parent] (Experience Bad Events): Count - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__exp__bad_count__v04(
data,
name = "mh_p_ple__exp__bad_count__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Good Events): Count [Validation: No more than 5 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__good_count
Life Events [Parent] (Experience Good Events): Count [Validation: No
more than 5 events missing and no experience items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__exp__good_count(
data,
name = "mh_p_ple__exp__good_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Good Events): Count - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__good_count__v01
Life Events [Parent] (Experience Good Events): Count - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__exp__good_count__v01(
data,
name = "mh_p_ple__exp__good_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Good Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__good_count__v02
Life Events [Parent] (Experience Good Events): Count - Version 2 (Year
4 and Year 5) [Validation: No more than 6 events missing and no experience
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__exp__good_count__v02(
data,
name = "mh_p_ple__exp__good_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Good Events): Count - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__good_count__v03
Life Events [Parent] (Experience Good Events): Count - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__exp__good_count__v03(
data,
name = "mh_p_ple__exp__good_count__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience Good Events): Count - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_p_ple__exp__good_count__v04
Life Events [Parent] (Experience Good Events): Count - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__exp__good_count__v04(
data,
name = "mh_p_ple__exp__good_count__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience): Number missing"
Description
Computes the summary score mh_p_ple__exp_nm
Life Events [Parent] (Experience): Number missing
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__exp_nm(data, name = "mh_p_ple__exp_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_p_ple__exp_nm__v01
Life Events [Parent] (Experience): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__exp_nm__v01(
data,
name = "mh_p_ple__exp_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_p_ple__exp_nm__v02
Life Events [Parent] (Experience): Number missing - Version 2 (Year 4
and Year 5)
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__exp_nm__v02(
data,
name = "mh_p_ple__exp_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience): Number missing - Version 3 (Year 6 )"
Description
Computes the summary score mh_p_ple__exp_nm__v03
Life Events [Parent] (Experience): Number missing - Version 3 (Year
6 )
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__exp_nm__v03(
data,
name = "mh_p_ple__exp_nm__v03",
events = "ses-06A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Experience): Number missing - Version 4 (Starting at Year 7)"
Description
Computes the summary score mh_p_ple__exp_nm__v04
Life Events [Parent] (Experience): Number missing - Version 4
(Starting at Year 7)
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__exp_nm__v04(
data,
name = "mh_p_ple__exp_nm__v04",
events = "ses-07A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Mean [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_mean
Life Events [Parent] (Severity of Bad Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__severity__bad_mean(
data,
name = "mh_p_ple__severity__bad_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_mean__v01
Life Events [Parent] (Severity of Bad Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__severity__bad_mean__v01(
data,
name = "mh_p_ple__severity__bad_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_mean__v02
Life Events [Parent] (Severity of Bad Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__severity__bad_mean__v02(
data,
name = "mh_p_ple__severity__bad_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Mean - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_mean__v03
Life Events [Parent] (Severity of Bad Events): Mean - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__severity__bad_mean__v03(
data,
name = "mh_p_ple__severity__bad_mean__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Mean - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_mean__v04
Life Events [Parent] (Severity of Bad Events): Mean - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__severity__bad_mean__v04(
data,
name = "mh_p_ple__severity__bad_mean__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Sum [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_sum
Life Events [Parent] (Severity of Bad Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__severity__bad_sum(
data,
name = "mh_p_ple__severity__bad_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_sum__v01
Life Events [Parent] (Severity of Bad Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__severity__bad_sum__v01(
data,
name = "mh_p_ple__severity__bad_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_sum__v02
Life Events [Parent] (Severity of Bad Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__severity__bad_sum__v02(
data,
name = "mh_p_ple__severity__bad_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Sum - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_sum__v03
Life Events [Parent] (Severity of Bad Events): Sum - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__severity__bad_sum__v03(
data,
name = "mh_p_ple__severity__bad_sum__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Bad Events): Sum - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__bad_sum__v04
Life Events [Parent] (Severity of Bad Events): Sum - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__severity__bad_sum__v04(
data,
name = "mh_p_ple__severity__bad_sum__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Mean [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_mean
Life Events [Parent] (Severity of Good Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__severity__good_mean(
data,
name = "mh_p_ple__severity__good_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_mean__v01
Life Events [Parent] (Severity of Good Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__severity__good_mean__v01(
data,
name = "mh_p_ple__severity__good_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_mean__v02
Life Events [Parent] (Severity of Good Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__severity__good_mean__v02(
data,
name = "mh_p_ple__severity__good_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Mean - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_mean__v03
Life Events [Parent] (Severity of Good Events): Mean - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__severity__good_mean__v03(
data,
name = "mh_p_ple__severity__good_mean__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Mean - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_mean__v04
Life Events [Parent] (Severity of Good Events): Mean - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__severity__good_mean__v04(
data,
name = "mh_p_ple__severity__good_mean__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Sum [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_sum
Life Events [Parent] (Severity of Good Events): Sum [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__severity__good_sum(
data,
name = "mh_p_ple__severity__good_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Mean [Validation: No more than 5 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_mean
Life Events [Parent] (Severity): Mean [Validation: No more than 5
events missing and no severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_p_ple__severity_mean(
data,
name = "mh_p_ple__severity_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_mean__v01
Life Events [Parent] (Severity): Mean - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_p_ple__severity_mean__v01(
data,
name = "mh_p_ple__severity_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_mean__v02
Life Events [Parent] (Severity): Mean - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
compute_mh_p_ple__severity_mean__v02(
data,
name = "mh_p_ple__severity_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Mean - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_mean__v03
Life Events [Parent] (Severity): Mean - Version 3 (Year 6 )
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_p_ple__severity_mean__v03(
data,
name = "mh_p_ple__severity_mean__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Mean - Version 4 (Starting at Year 7) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_mean__v04
Life Events [Parent] (Severity): Mean - Version 4 (Starting at Year 7)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
compute_mh_p_ple__severity_mean__v04(
data,
name = "mh_p_ple__severity_mean__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Number missing"
Description
Computes the summary score mh_p_ple__severity_nm
Life Events [Parent] (Severity): Number missing
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__severity_nm(
data,
name = "mh_p_ple__severity_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_p_ple__severity_nm__v01
Life Events [Parent] (Severity): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__severity_nm__v01(
data,
name = "mh_p_ple__severity_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_p_ple__severity_nm__v02
Life Events [Parent] (Severity): Number missing - Version 2 (Year 4
and Year 5)
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__severity_nm__v02(
data,
name = "mh_p_ple__severity_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Number missing - Version 3 (Year 6 )"
Description
Computes the summary score mh_p_ple__severity_nm__v03
Life Events [Parent] (Severity): Number missing - Version 3 (Year 6 )
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__severity_nm__v03(
data,
name = "mh_p_ple__severity_nm__v03",
events = "ses-06A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Number missing - Version 4 (Starting at Year 7)"
Description
Computes the summary score mh_p_ple__severity_nm__v04
Life Events [Parent] (Severity): Number missing - Version 4 (Starting
at Year 7)
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple__severity_nm__v04(
data,
name = "mh_p_ple__severity_nm__v04",
events = "ses-07A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for mh_p_ple
Description
This function computes all summary scores for the mh_p_ple form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_ple_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_ple_all(data)
## End(Not run)
Compute "Life Events [Parent] (Events): Number missing"
Description
Computes the summary score mh_p_ple_nm
Life Events [Parent] (Events): Number missing
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple_nm(data, name = "mh_p_ple_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_p_ple_nm__v01
Life Events [Parent] (Events): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple_nm__v01(
data,
name = "mh_p_ple_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_p_ple_nm__v02
Life Events [Parent] (Events): Number missing - Version 2 (Year 4 and
Year 5)
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
mh_p_ple_032
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple_nm__v02(
data,
name = "mh_p_ple_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Number missing - Version 3 (Year 6 )"
Description
Computes the summary score mh_p_ple_nm__v03
Life Events [Parent] (Events): Number missing - Version 3 (Year 6 )
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
mh_p_ple_032
-
mh_p_ple_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple_nm__v03(
data,
name = "mh_p_ple_nm__v03",
events = "ses-06A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Number missing - Version 4 (Starting at Year 7)"
Description
Computes the summary score mh_p_ple_nm__v04
Life Events [Parent] (Events): Number missing - Version 4 (Starting at
Year 7)
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_032
-
mh_p_ple_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_p_ple_nm__v04(
data,
name = "mh_p_ple_nm__v04",
events = "ses-07A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for mh_p_ssrs.
Description
This function computes all summary scores for the mh_p_ssrs table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_p_ssrs_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_p_ssrs_all(data)
## End(Not run)
Compute "Short Social Responsiveness Scale [Parent]: Sum"
Description
Computes the summary score mh_p_ssrs_sum
Short Social Responsiveness Scale [Parent]: Sum
-
Summarized variables:
-
mh_p_ssrs_001
-
mh_p_ssrs_002
-
mh_p_ssrs_003
-
mh_p_ssrs_004
-
mh_p_ssrs_005
-
mh_p_ssrs_006
-
mh_p_ssrs_007
-
mh_p_ssrs_008
-
mh_p_ssrs_009
-
mh_p_ssrs_010
-
mh_p_ssrs_011
-
-
Excluded values: none
-
Validation criterion: none of 11 items missing
Usage
compute_mh_p_ssrs_sum(
data,
name = "mh_p_ssrs_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_p_ssrs_sum(data) |>
select(
any_of(c("mh_p_ssrs_sum", vars_mh_p_ssrs))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Attention): Sum"
Description
Computes the summary score mh_t_bpm__attn_sum
Brief Problem Monitor [Teacher] (Attention): Sum
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__attn_sum(
data,
name = "mh_t_bpm__attn_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__attn_sum(data) |>
select(
any_of(c("mh_t_bpm__attn_sum", vars_mh_t_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Attention): T-score"
Description
Computes the summary score mh_t_bpm__attn_tscore
Brief Problem Monitor [Teacher] (Attention): T-score
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__attn_tscore(
data,
data_norm = NULL,
name = "mh_t_bpm__attn_tscore",
col_age = "mh_t_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__attn_tscore(data) |>
select(
any_of(c("mh_t_bpm__attn_tscore", vars_mh_t_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Externalizing): Sum"
Description
Computes the summary score mh_t_bpm__ext_sum
Brief Problem Monitor [Teacher] (Externalizing): Sum
-
Summarized variables:
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__ext_sum(
data,
name = "mh_t_bpm__ext_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__ext_sum(data) |>
select(
any_of(c("mh_t_bpm__ext_sum", vars_mh_t_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Externalizing): T-score"
Description
Computes the summary score mh_t_bpm__ext_tscore
Brief Problem Monitor [Teacher] (Externalizing): T-score
-
Summarized variables:
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__ext_tscore(
data,
data_norm = NULL,
name = "mh_t_bpm__ext_tscore",
col_age = "mh_t_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__ext_tscore(data) |>
select(
any_of(c("mh_t_bpm__ext_tscore", vars_mh_t_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Internalizing): Sum"
Description
Computes the summary score mh_t_bpm__int_sum
Brief Problem Monitor [Teacher] (Internalizing): Sum
-
Summarized variables:
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__int_sum(
data,
name = "mh_t_bpm__int_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__int_sum(data) |>
select(
any_of(c("mh_t_bpm__int_sum", vars_mh_t_bpm__int))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Internalizing): T-score"
Description
Computes the summary score mh_t_bpm__int_tscore
Brief Problem Monitor [Teacher] (Internalizing): T-score
-
Summarized variables:
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_t_bpm__int_tscore(
data,
data_norm = NULL,
name = "mh_t_bpm__int_tscore",
col_age = "mh_t_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm__int_tscore(data) |>
select(
any_of(c("mh_t_bpm__int_tscore", vars_mh_t_bpm__int))
)
## End(Not run)
Compute all summary scores for mh_t_bpm.
Description
This function computes all summary scores for the mh_t_bpm form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_t_bpm_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_t_bpm_all(data)
## End(Not run)
Compute "Brief Problem Monitor [Teacher]: Sum"
Description
Computes the summary score mh_t_bpm_sum
Brief Problem Monitor [Teacher]: Sum
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 18 items missing
Usage
compute_mh_t_bpm_sum(
data,
name = "mh_t_bpm_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm_sum(data) |>
select(
any_of(c("mh_t_bpm_sum", vars_mh_t_bpm))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher]: T-score"
Description
Computes the summary score mh_t_bpm_tscore
Brief Problem Monitor [Teacher]: T-score
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 18 items missing
Usage
compute_mh_t_bpm_tscore(
data,
data_norm = NULL,
name = "mh_t_bpm_tscore",
col_age = "mh_t_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_t_bpm_tscore(data) |>
select(
any_of(c("mh_t_bpm_tscore", vars_mh_t_bpm))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Drive): Sum"
Description
Computes the summary score mh_y_bisbas__bas__dr_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Drive): Sum
-
Summarized variables:
-
mh_y_bisbas__bas__dr_001
-
mh_y_bisbas__bas__dr_002
-
mh_y_bisbas__bas__dr_003
-
mh_y_bisbas__bas__dr_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_bisbas__bas__dr_sum(
data,
name = "mh_y_bisbas__bas__dr_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_bisbas__bas__dr_nm()
Examples
## Not run:
compute_mh_y_bisbas__bas__dr_sum(data) |>
select(
any_of(c("mh_y_bisbas__bas__dr_sum", vars_mh_y_bisbas__bas__dr))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Fun Seeking): Sum"
Description
Computes the summary score mh_y_bisbas__bas__fs_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Fun Seeking): Sum
-
Summarized variables:
-
mh_y_bisbas__bas__fs_001
-
mh_y_bisbas__bas__fs_002
-
mh_y_bisbas__bas__fs_003
-
mh_y_bisbas__bas__fs_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_bisbas__bas__fs_sum(
data,
name = "mh_y_bisbas__bas__fs_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_bisbas__bas__fs_nm()
Examples
## Not run:
compute_mh_y_bisbas__bas__fs_sum(data) |>
select(
any_of(c("mh_y_bisbas__bas__fs_sum", vars_mh_y_bisbas__bas__fs))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Reward Responsiveness): Sum"
Description
Computes the summary score mh_y_bisbas__bas__rr_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Reward Responsiveness): Sum
-
Summarized variables:
-
mh_y_bisbas__bas__rr_001
-
mh_y_bisbas__bas__rr_002
-
mh_y_bisbas__bas__rr_003
-
mh_y_bisbas__bas__rr_004
-
mh_y_bisbas__bas__rr_005
-
-
Excluded values: none
-
Validation criterion: none of 5 items missing
Usage
compute_mh_y_bisbas__bas__rr_sum(
data,
name = "mh_y_bisbas__bas__rr_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_bisbas__bas__rr_nm()
Examples
## Not run:
compute_mh_y_bisbas__bas__rr_sum(data) |>
select(
any_of(c("mh_y_bisbas__bas__rr_sum", vars_mh_y_bisbas__bas__rr))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] ((BAS Reward Responsiveness (modified)): Sum"
Description
Computes the summary score mh_y_bisbas__bas__rr_sum__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] ((BAS Reward Responsiveness (modified)): Sum
-
Summarized variables:
-
mh_y_bisbas__bas__rr_001
-
mh_y_bisbas__bas__rr_002
-
mh_y_bisbas__bas__rr_004
-
mh_y_bisbas__bas__rr_005
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_bisbas__bas__rr_sum__v01(
data,
name = "mh_y_bisbas__bas__rr_sum__v01",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_bisbas__bas__rr_nm__v01()
Examples
## Not run:
compute_mh_y_bisbas__bas__rr_sum__v01(data) |>
select(
any_of(c("mh_y_bisbas__bas__rr_sum__v01", vars_mh_y_bisbas__bas__rr__v01))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BIS): Sum"
Description
Computes the summary score mh_y_bisbas__bis_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS): Sum
-
Summarized variables:
-
mh_y_bisbas__bis_001
-
mh_y_bisbas__bis_002
-
mh_y_bisbas__bis_003
-
mh_y_bisbas__bis_004
-
mh_y_bisbas__bis_005
-
mh_y_bisbas__bis_006
-
mh_y_bisbas__bis_007
-
-
Excluded values: none
-
Validation criterion: none of 7 items missing
Usage
compute_mh_y_bisbas__bis_sum(
data,
name = "mh_y_bisbas__bis_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bisbas__bis_sum(data) |>
select(
any_of(c("mh_y_bisbas__bis_sum", vars_mh_y_bisbas__bis))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BIS (modified)): Sum"
Description
Computes the summary score mh_y_bisbas__bis_sum__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS (modified)): Sum
-
Summarized variables:
-
mh_y_bisbas__bis_002
-
mh_y_bisbas__bis_003
-
mh_y_bisbas__bis_004
-
mh_y_bisbas__bis_006
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_bisbas__bis_sum__v01(
data,
name = "mh_y_bisbas__bis_sum__v01",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_bisbas__bis_nm__v01()
Examples
## Not run:
compute_mh_y_bisbas__bis_sum__v01(data) |>
select(
any_of(c("mh_y_bisbas__bis_sum__v01", vars_mh_y_bisbas__bis__v01))
)
## End(Not run)
Compute all summary scores for mh_y_bisbas.
Description
This function computes all summary scores for the mh_y_bisbas table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_bisbas_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_bisbas_all(data)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Attention): Sum"
Description
Computes the summary score mh_y_bpm__attn_sum
Brief Problem Monitor [Youth] (Attention): Sum
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_y_bpm__attn_sum(
data,
name = "mh_y_bpm__attn_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__attn_sum(data) |>
select(
any_of(c("mh_y_bpm__attn_sum", vars_mh_y_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Attention): T-score"
Description
Computes the summary score mh_y_bpm__attn_tscore
Brief Problem Monitor [Youth] (Attention): T-score
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_y_bpm__attn_tscore(
data,
data_norm = NULL,
name = "mh_y_bpm__attn_tscore",
col_age = "mh_y_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__attn_tscore(data) |>
select(
any_of(c("mh_y_bpm__attn_tscore", vars_mh_y_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Externalizing): Sum"
Description
Computes the summary score mh_y_bpm__ext_sum
Brief Problem Monitor [Youth] (Externalizing): Sum
-
Summarized variables:
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_bpm__ext_sum(
data,
name = "mh_y_bpm__ext_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__ext_sum(data) |>
select(
any_of(c("mh_y_bpm__ext_sum", vars_mh_y_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Externalizing): T-score"
Description
Computes the summary score mh_y_bpm__ext_tscore
Brief Problem Monitor [Youth] (Externalizing): T-score
-
Summarized variables:
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_bpm__ext_tscore(
data,
data_norm = NULL,
name = "mh_y_bpm__ext_tscore",
col_age = "mh_y_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__ext_tscore(data) |>
select(
any_of(c("mh_y_bpm__ext_tscore", vars_mh_y_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Internalizing): Sum"
Description
Computes the summary score mh_y_bpm__int_sum
Brief Problem Monitor [Youth] (Internalizing): Sum
-
Summarized variables:
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_y_bpm__int_sum(
data,
name = "mh_y_bpm__int_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__int_sum(data) |>
select(
any_of(c("mh_y_bpm__int_sum", vars_mh_y_bpm__int))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Internalizing): T-score"
Description
Computes the summary score mh_y_bpm__int_tscore
Brief Problem Monitor [Youth] (Internalizing): T-score
-
Summarized variables:
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 6 items missing
Usage
compute_mh_y_bpm__int_tscore(
data,
data_norm = NULL,
name = "mh_y_bpm__int_tscore",
col_age = "mh_y_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm__int_tscore(data) |>
select(
any_of(c("mh_y_bpm__int_tscore", vars_mh_y_bpm__int))
)
## End(Not run)
Compute all summary scores for mh_y_bpm.
Description
This function computes all summary scores for the mh_y_bpm form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_bpm_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_bpm_all(data)
## End(Not run)
Compute "Brief Problem Monitor [Youth]: Sum"
Description
Computes the summary score mh_y_bpm_sum
Brief Problem Monitor [Youth]: Sum
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 19 items missing
Usage
compute_mh_y_bpm_sum(
data,
name = "mh_y_bpm_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm_sum(data) |>
select(
any_of(c("mh_y_bpm_sum", vars_mh_y_bpm))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth]: T-score"
Description
Computes the summary score mh_y_bpm_tscore
Brief Problem Monitor [Youth]: T-score
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 19 items missing
Usage
compute_mh_y_bpm_tscore(
data,
data_norm = NULL,
name = "mh_y_bpm_tscore",
col_age = "mh_y_bpm_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_bpm_tscore(data) |>
select(
any_of(c("mh_y_bpm_tscore", vars_mh_y_bpm))
)
## End(Not run)
Compute "Emotion Regulation Questionnaire [Youth] (Reappraisal): Number missing"
Description
Computes the summary score mh_y_erq__reapp_nm
Emotion Regulation Questionnaire [Youth] (Reappraisal): Number missing
-
Summarized variables:
-
mh_y_erq__reapp_001
-
mh_y_erq__reapp_002
-
mh_y_erq__reapp_003
-
-
Excluded values:
777
Usage
compute_mh_y_erq__reapp_nm(
data,
name = "mh_y_erq__reapp_nm",
exclude = c("777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_erq__reapp_mean()
Examples
## Not run:
compute_mh_y_erq__reapp_nm(data) |>
select(
any_of(c("mh_y_erq__reapp_nm", vars_mh_y_erq__reapp))
)
## End(Not run)
Compute "Emotion Regulation Questionnaire [Youth] (Suppression): Number missing"
Description
Computes the summary score mh_y_erq__suppr_nm
Emotion Regulation Questionnaire [Youth] (Suppression): Number missing
-
Summarized variables:
-
mh_y_erq__suppr_001
-
mh_y_erq__suppr_002
-
mh_y_erq__suppr_003
-
-
Excluded values:
777
Usage
compute_mh_y_erq__suppr_nm(
data,
name = "mh_y_erq__suppr_nm",
exclude = c("777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_erq__suppr_mean()
Examples
## Not run:
compute_mh_y_erq__suppr_nm(data) |>
select(
any_of(c("mh_y_erq__suppr_nm", vars_mh_y_erq__suppr))
)
## End(Not run)
Compute all summary scores for mh_y_erq.
Description
This function computes all summary scores for the mh_y_erq table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_erq_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_erq_all(data)
## End(Not run)
Compute all summary scores for mh_y_upps.
Description
This function computes all summary scores for the mh_y_pai table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_pai_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_pai_all(data)
## End(Not run)
Compute "NIH Toolbox - Positive Affect Items [Youth] (NA): Sum [Validation: None missing or declined]"
Description
Computes the summary score mh_y_pai_sum
NIH Toolbox - Positive Affect Items [Youth] (NA): Sum [Validation:
None missing or declined]
-
Summarized variables:
-
mh_y_pai_001
-
mh_y_pai_002
-
mh_y_pai_003
-
mh_y_pai_004
-
mh_y_pai_005
-
mh_y_pai_006
-
mh_y_pai_007
-
mh_y_pai_008
-
mh_y_pai_009
-
-
Excluded values:
777
999
-
Validation criterion: none of 9 items missing
Usage
compute_mh_y_pai_sum(
data,
name = "mh_y_pai_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_pai_sum(data) |>
select(
any_of(c("mh_y_pai_sum", vars_mh_y_pai))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Overt Aggression): Sum"
Description
Computes the summary score mh_y_peq__overt__agg_sum
Peer Experiences Questionnaire [Youth] (Overt Aggression): Sum
-
Summarized variables:
-
mh_y_peq__overt__agg_001
-
mh_y_peq__overt__agg_002
-
mh_y_peq__overt__agg_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__overt__agg_sum(
data,
name = "mh_y_peq__overt__agg_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__overt__agg_nm()
Examples
## Not run:
compute_mh_y_peq__overt__agg_sum(data) |>
select(
any_of(c("mh_y_peq__overt__agg_sum", vars_mh_y_peq__overt__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Overt Victimization): Sum"
Description
Computes the summary score mh_y_peq__overt__vict_sum
Peer Experiences Questionnaire [Youth] (Overt Victimization): Sum
-
Summarized variables:
-
mh_y_peq__overt__vict_001
-
mh_y_peq__overt__vict_002
-
mh_y_peq__overt__vict_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__overt__vict_sum(
data,
name = "mh_y_peq__overt__vict_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__overt__vict_nm()
Examples
## Not run:
compute_mh_y_peq__overt__vict_sum(data) |>
select(
any_of(c("mh_y_peq__overt__vict_sum", vars_mh_y_peq__overt__vict))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Relational Aggression): Sum"
Description
Computes the summary score mh_y_peq__rel__agg_sum
Peer Experiences Questionnaire [Youth] (Relational Aggression): Sum
-
Summarized variables:
-
mh_y_peq__rel__agg_001
-
mh_y_peq__rel__agg_002
-
mh_y_peq__rel__agg_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__rel__agg_sum(
data,
name = "mh_y_peq__rel__agg_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__rel__agg_nm()
Examples
## Not run:
compute_mh_y_peq__rel__agg_sum(data) |>
select(
any_of(c("mh_y_peq__rel__agg_sum", vars_mh_y_peq__rel__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Relational Victimization): Sum"
Description
Computes the summary score mh_y_peq__rel__vict_sum
Peer Experiences Questionnaire [Youth] (Relational Victimization): Sum
-
Summarized variables:
-
mh_y_peq__rel__vict_001
-
mh_y_peq__rel__vict_002
-
mh_y_peq__rel__vict_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__rel__vict_sum(
data,
name = "mh_y_peq__rel__vict_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__rel__vict_nm()
Examples
## Not run:
compute_mh_y_peq__rel__vict_sum(data) |>
select(
any_of(c("mh_y_peq__rel__vict_sum", vars_mh_y_peq__rel__vict))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Reputational Aggression): Sum"
Description
Computes the summary score mh_y_peq__rep__agg_sum
Peer Experiences Questionnaire [Youth] (Reputational Aggression): Sum
-
Summarized variables:
-
mh_y_peq__rep__agg_001
-
mh_y_peq__rep__agg_002
-
mh_y_peq__rep__agg_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__rep__agg_sum(
data,
name = "mh_y_peq__rep__agg_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__rep__agg_nm()
Examples
## Not run:
compute_mh_y_peq__rep__agg_sum(data) |>
select(
any_of(c("mh_y_peq__rep__agg_sum", vars_mh_y_peq__rep__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Reputational Victimization): Sum"
Description
Computes the summary score mh_y_peq__rep__vict_sum
Peer Experiences Questionnaire [Youth] (Reputational Victimization):
Sum
-
Summarized variables:
-
mh_y_peq__rep__vict_001
-
mh_y_peq__rep__vict_002
-
mh_y_peq__rep__vict_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
compute_mh_y_peq__rep__vict_sum(
data,
name = "mh_y_peq__rep__vict_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_peq__rep__vict_nm()
Examples
## Not run:
compute_mh_y_peq__rep__vict_sum(data) |>
select(
any_of(c("mh_y_peq__rep__vict_sum", vars_mh_y_peq__rep__vict))
)
## End(Not run)
Compute all summary scores for mh_y_peq.
Description
This function computes all summary scores for the mh_y_peq table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_peq_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_peq_all(data)
## End(Not run)
Compute "Life Events [Youth] (Experience Bad Events): Count [Validation: No more than 5 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__bad_count
Life Events [Youth] (Experience Bad Events): Count [Validation: No
more than 5 events missing and no experience items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__exp__bad_count(
data,
name = "mh_y_ple__exp__bad_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Bad Events): Count - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__bad_count__v01
Life Events [Youth] (Experience Bad Events): Count - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__exp__bad_count__v01(
data,
name = "mh_y_ple__exp__bad_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Bad Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__bad_count__v02
Life Events [Youth] (Experience Bad Events): Count - Version 2 (Year
4 and Year 5) [Validation: No more than 6 events missing and no experience
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__exp__bad_count__v02(
data,
name = "mh_y_ple__exp__bad_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Bad Events): Count - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__bad_count__v03
Life Events [Youth] (Experience Bad Events): Count - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__exp__bad_count__v03(
data,
name = "mh_y_ple__exp__bad_count__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Good Events): Count [Validation: No more than 5 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__good_count
Life Events [Youth] (Experience Good Events): Count [Validation: No
more than 5 events missing and no experience items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__exp__good_count(
data,
name = "mh_y_ple__exp__good_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Good Events): Count - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__good_count__v01
Life Events [Youth] (Experience Good Events): Count - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience items
missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__exp__good_count__v01(
data,
name = "mh_y_ple__exp__good_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Good Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__good_count__v02
Life Events [Youth] (Experience Good Events): Count - Version 2 (Year
4 and Year 5) [Validation: No more than 6 events missing and no experience
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__exp__good_count__v02(
data,
name = "mh_y_ple__exp__good_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience Good Events): Count - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience items missing or declined]"
Description
Computes the summary score mh_y_ple__exp__good_count__v03
Life Events [Youth] (Experience Good Events): Count - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__exp__good_count__v03(
data,
name = "mh_y_ple__exp__good_count__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience): Number missing"
Description
Computes the summary score mh_y_ple__exp_nm
Life Events [Youth] (Experience): Number missing
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__exp_nm(data, name = "mh_y_ple__exp_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_y_ple__exp_nm__v01
Life Events [Youth] (Experience): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__exp_nm__v01(
data,
name = "mh_y_ple__exp_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_y_ple__exp_nm__v02
Life Events [Youth] (Experience): Number missing - Version 2 (Year 4
and Year 5)
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__exp_nm__v02(
data,
name = "mh_y_ple__exp_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Experience): Number missing - Version 3 (Starting at Year 6)"
Description
Computes the summary score mh_y_ple__exp_nm__v03
Life Events [Youth] (Experience): Number missing - Version 3 (Starting
at Year 6)
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__exp_nm__v03(
data,
name = "mh_y_ple__exp_nm__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Mean [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_mean
Life Events [Youth] (Severity of Bad Events): Mean [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__severity__bad_mean(
data,
name = "mh_y_ple__severity__bad_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_mean__v01
Life Events [Youth] (Severity of Bad Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__severity__bad_mean__v01(
data,
name = "mh_y_ple__severity__bad_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_mean__v02
Life Events [Youth] (Severity of Bad Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__bad_mean__v02(
data,
name = "mh_y_ple__severity__bad_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Mean - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_mean__v03
Life Events [Youth] (Severity of Bad Events): Mean - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__bad_mean__v03(
data,
name = "mh_y_ple__severity__bad_mean__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Sum [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_sum
Life Events [Youth] (Severity of Bad Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__severity__bad_sum(
data,
name = "mh_y_ple__severity__bad_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_sum__v01
Life Events [Youth] (Severity of Bad Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__severity__bad_sum__v01(
data,
name = "mh_y_ple__severity__bad_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_sum__v02
Life Events [Youth] (Severity of Bad Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__bad_sum__v02(
data,
name = "mh_y_ple__severity__bad_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Bad Events): Sum - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__bad_sum__v03
Life Events [Youth] (Severity of Bad Events): Sum - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__bad_sum__v03(
data,
name = "mh_y_ple__severity__bad_sum__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Mean [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_mean
Life Events [Youth] (Severity of Good Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__severity__good_mean(
data,
name = "mh_y_ple__severity__good_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_mean__v01
Life Events [Youth] (Severity of Good Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__severity__good_mean__v01(
data,
name = "mh_y_ple__severity__good_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_mean__v02
Life Events [Youth] (Severity of Good Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__good_mean__v02(
data,
name = "mh_y_ple__severity__good_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Mean - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_mean__v03
Life Events [Youth] (Severity of Good Events): Mean - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity__good_mean__v03(
data,
name = "mh_y_ple__severity__good_mean__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Mean [Validation: No more than 5 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_mean
Life Events [Youth] (Severity): Mean [Validation: No more than 5
events missing and no severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
compute_mh_y_ple__severity_mean(
data,
name = "mh_y_ple__severity_mean",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Mean - Version 1 (Year 3) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_mean__v01
Life Events [Youth] (Severity): Mean - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
compute_mh_y_ple__severity_mean__v01(
data,
name = "mh_y_ple__severity_mean__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Mean - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_mean__v02
Life Events [Youth] (Severity): Mean - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
compute_mh_y_ple__severity_mean__v02(
data,
name = "mh_y_ple__severity_mean__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Mean - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_mean__v03
Life Events [Youth] (Severity): Mean - Version 3 (Starting at Year 6)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 34 items missing
Usage
compute_mh_y_ple__severity_mean__v03(
data,
name = "mh_y_ple__severity_mean__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Number missing"
Description
Computes the summary score mh_y_ple__severity_nm
Life Events [Youth] (Severity): Number missing
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__severity_nm(
data,
name = "mh_y_ple__severity_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_y_ple__severity_nm__v01
Life Events [Youth] (Severity): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__severity_nm__v01(
data,
name = "mh_y_ple__severity_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_y_ple__severity_nm__v02
Life Events [Youth] (Severity): Number missing - Version 2 (Year 4 and
Year 5)
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__severity_nm__v02(
data,
name = "mh_y_ple__severity_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Number missing - Version 3 (Starting at Year 6)"
Description
Computes the summary score mh_y_ple__severity_nm__v03
Life Events [Youth] (Severity): Number missing - Version 3 (Starting
at Year 6)
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple__severity_nm__v03(
data,
name = "mh_y_ple__severity_nm__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for mh_y_ple
Description
This function computes all summary scores for the mh_y_ple form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_ple_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_ple_all(data)
## End(Not run)
Compute "Life Events [Youth] (Events): Number missing"
Description
Computes the summary score mh_y_ple_nm
Life Events [Youth] (Events): Number missing
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple_nm(data, name = "mh_y_ple_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Number missing - Version 1 (Year 3)"
Description
Computes the summary score mh_y_ple_nm__v01
Life Events [Youth] (Events): Number missing - Version 1 (Year 3)
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple_nm__v01(
data,
name = "mh_y_ple_nm__v01",
events = "ses-03A",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Number missing - Version 2 (Year 4 and Year 5)"
Description
Computes the summary score mh_y_ple_nm__v02
Life Events [Youth] (Events): Number missing - Version 2 (Year 4 and
Year 5)
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
mh_y_ple_032
-
mh_y_ple_034
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple_nm__v02(
data,
name = "mh_y_ple_nm__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Number missing - Version 3 (Starting at Year 6)"
Description
Computes the summary score mh_y_ple_nm__v03
Life Events [Youth] (Events): Number missing - Version 3 (Starting at
Year 6)
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
mh_y_ple_032
-
mh_y_ple_033
-
mh_y_ple_034
-
-
Excluded values:
444
777
999
Usage
compute_mh_y_ple_nm__v03(
data,
name = "mh_y_ple_nm__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Prodromal Psychosis Scale [Youth] (Bother "No" responses): Count"
Description
Computes the summary score mh_y_pps__bother__no_count
Prodromal Psychosis Scale [Youth] (Bother
-
Summarized variables:
-
mh_y_pps__bother_001
-
mh_y_pps__bother_002
-
mh_y_pps__bother_003
-
mh_y_pps__bother_004
-
mh_y_pps__bother_005
-
mh_y_pps__bother_006
-
mh_y_pps__bother_007
-
mh_y_pps__bother_008
-
mh_y_pps__bother_009
-
mh_y_pps__bother_010
-
mh_y_pps__bother_011
-
mh_y_pps__bother_012
-
mh_y_pps__bother_013
-
mh_y_pps__bother_014
-
mh_y_pps__bother_015
-
mh_y_pps__bother_016
-
mh_y_pps__bother_017
-
mh_y_pps__bother_018
-
mh_y_pps__bother_019
-
mh_y_pps__bother_020
-
mh_y_pps__bother_021
-
-
Excluded values: none
-
Validation criterion: 0 of 21 items missing
Usage
compute_mh_y_pps__bother__no_count(
data,
name = "mh_y_pps__bother__no_count",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Details
The bother count is depend on the mh_y_pps__bother_nm
score. If the
mh_y_pps__bother_nm
score is greater than max_na
, the bother count
is set to NA
.
There is also a sanity check for the gating question in PPS bother score.
If the paired gating question is 0 or NA
and the bother score is not
missing, the paired bother score is set to NA
before computing the count.
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_mh_y_pps__bother__no_count(data) |>
select(
any_of(c("mh_y_pps__bother__no_count", vars_mh_y_pps__bother))
)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (Bother "Yes" responses): Count"
Description
Computes the summary score mh_y_pps__bother__yes_count
Prodromal Psychosis Scale [Youth] (Bother
-
Summarized variables:
-
mh_y_pps__bother_001
-
mh_y_pps__bother_002
-
mh_y_pps__bother_003
-
mh_y_pps__bother_004
-
mh_y_pps__bother_005
-
mh_y_pps__bother_006
-
mh_y_pps__bother_007
-
mh_y_pps__bother_008
-
mh_y_pps__bother_009
-
mh_y_pps__bother_010
-
mh_y_pps__bother_011
-
mh_y_pps__bother_012
-
mh_y_pps__bother_013
-
mh_y_pps__bother_014
-
mh_y_pps__bother_015
-
mh_y_pps__bother_016
-
mh_y_pps__bother_017
-
mh_y_pps__bother_018
-
mh_y_pps__bother_019
-
mh_y_pps__bother_020
-
mh_y_pps__bother_021
-
-
Excluded values: none
-
Validation criterion: 0 of 21 items missing
Usage
compute_mh_y_pps__bother__yes_count(
data,
name = "mh_y_pps__bother__yes_count",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Details
The bother count is depend on the mh_y_pps__bother_nm
score. If the
mh_y_pps__bother_nm
score is greater than max_na
, the bother count
is set to NA
.
There is also a sanity check for the gating question in PPS bother score.
If the paired gating question is 0 or NA
and the bother score is not
missing, the paired bother score is set to NA
before computing the count.
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_mh_y_pps__bother__yes_count(data) |>
select(
any_of(c("mh_y_pps__bother__yes_count", vars_mh_y_pps__bother))
)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (Severity Score): Mean"
Description
Computes the summary score mh_y_pps__severity_mean
Prodromal Psychosis Scale [Youth] (Severity Score): Mean
-
Summarized variables:
-
mh_y_pps_001
-
mh_y_pps_002
-
mh_y_pps_003
-
mh_y_pps_004
-
mh_y_pps_005
-
mh_y_pps_006
-
mh_y_pps_007
-
mh_y_pps_008
-
mh_y_pps_009
-
mh_y_pps_010
-
mh_y_pps_011
-
mh_y_pps_012
-
mh_y_pps_013
-
mh_y_pps_014
-
mh_y_pps_015
-
mh_y_pps_016
-
mh_y_pps_017
-
mh_y_pps_018
-
mh_y_pps_019
-
mh_y_pps_020
-
mh_y_pps_021
-
mh_y_pps__severity_001
-
mh_y_pps__severity_002
-
mh_y_pps__severity_003
-
mh_y_pps__severity_004
-
mh_y_pps__severity_005
-
mh_y_pps__severity_006
-
mh_y_pps__severity_007
-
mh_y_pps__severity_008
-
mh_y_pps__severity_009
-
mh_y_pps__severity_010
-
mh_y_pps__severity_011
-
mh_y_pps__severity_012
-
mh_y_pps__severity_013
-
mh_y_pps__severity_014
-
mh_y_pps__severity_015
-
mh_y_pps__severity_016
-
mh_y_pps__severity_017
-
mh_y_pps__severity_018
-
mh_y_pps__severity_019
-
mh_y_pps__severity_020
-
mh_y_pps__severity_021
-
-
Excluded values: none
-
Validation criterion: none of 21 items missing
Usage
compute_mh_y_pps__severity_mean(
data,
name = "mh_y_pps__severity_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Details
The mean severity score is calculated by dividing the total severity
score by the number of mh_y_pps__bother__yes_count
. If any of the
two values is missing, the mean severity score is set to NA
.
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_mh_y_pps__bother__yes_count()
Examples
## Not run:
compute_mh_y_pps__severity_mean(data) |>
select(
any_of(c("mh_y_pps__severity_mean", vars_mh_y_pps__severity))
)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (Severity Score)"
Description
Computes the summary score mh_y_pps__severity_score
Prodromal Psychosis Scale [Youth] (Severity Score)
-
Summarized variables:
-
mh_y_pps__severity_001
-
mh_y_pps__severity_002
-
mh_y_pps__severity_003
-
mh_y_pps__severity_004
-
mh_y_pps__severity_005
-
mh_y_pps__severity_006
-
mh_y_pps__severity_007
-
mh_y_pps__severity_008
-
mh_y_pps__severity_009
-
mh_y_pps__severity_010
-
mh_y_pps__severity_011
-
mh_y_pps__severity_012
-
mh_y_pps__severity_013
-
mh_y_pps__severity_014
-
mh_y_pps__severity_015
-
mh_y_pps__severity_016
-
mh_y_pps__severity_017
-
mh_y_pps__severity_018
-
mh_y_pps__severity_019
-
mh_y_pps__severity_020
-
mh_y_pps__severity_021
-
-
Excluded values: none
-
Validation criterion: none of 21 items missing
Usage
compute_mh_y_pps__severity_score(
data,
name = "mh_y_pps__severity_score",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
combine |
logical. If |
Details
The severity score is calculated by summing the severity scores for each
question and adding the number of mh_y_pps__bother__yes_count
to the
total.
However, if the mh_y_pps__severity_nm
score is greater than max_na
,
the severity score is set to NA
.
There is also a sanity check for the gating question of PPS
base/bother score. If the paired base/bother question is 0 or NA
and the severity score is not missing, the paired severity score is set
to NA
before computing the score.
Value
tbl. see combine
.
See Also
compute_mh_y_pps__bother__yes_count()
Examples
## Not run:
compute_mh_y_pps__severity_score(data) |>
select(
any_of(c("mh_y_pps__severity_score", vars_mh_y_pps__severity))
) |>
View()
## End(Not run)
Compute all PPS scores
Description
This super function computes all scores in PPS using all the default arguments.
Usage
compute_mh_y_pps_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Details
Make sure the data
is the full set of all variables from MCTQ.
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_pps_all(data)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (number of responses): Number missing "
Description
Computes the summary score mh_y_pps_nm
Prodromal Psychosis Scale [Youth] (number of responses): Number
missing
-
Summarized variables:
-
mh_y_pps_001
-
mh_y_pps_002
-
mh_y_pps_003
-
mh_y_pps_004
-
mh_y_pps_005
-
mh_y_pps_006
-
mh_y_pps_007
-
mh_y_pps_008
-
mh_y_pps_009
-
mh_y_pps_010
-
mh_y_pps_011
-
mh_y_pps_012
-
mh_y_pps_013
-
mh_y_pps_014
-
mh_y_pps_015
-
mh_y_pps_016
-
mh_y_pps_017
-
mh_y_pps_018
-
mh_y_pps_019
-
mh_y_pps_020
-
mh_y_pps_021
-
Usage
compute_mh_y_pps_nm(data, name = "mh_y_pps_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_mh_y_pps_nm(data) |>
select(
any_of(c("mh_y_pps_nm", vars_mh_y_pps_count))
)
## End(Not run)
Compute all summary scores for mh_y_sup.
Description
This function computes all summary scores for the mh_y_sup table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_sup_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_sup_all(data)
## End(Not run)
Compute "7-Up Mania Inventory [Youth]: Sum"
Description
Computes the summary score mh_y_sup_sum
7-Up Mania Inventory [Youth]: Sum
-
Summarized variables:
-
mh_y_sup_001
-
mh_y_sup_002
-
mh_y_sup_003
-
mh_y_sup_004
-
mh_y_sup_005
-
mh_y_sup_006
-
mh_y_sup_007
-
-
Excluded values: none
-
Validation criterion: none of 7 items missing
Usage
compute_mh_y_sup_sum(
data,
name = "mh_y_sup_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_sup_sum(data) |>
select(
any_of(c("mh_y_sup_sum", vars_mh_y_sup))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative Urgency): Sum"
Description
Computes the summary score mh_y_upps__nurg_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative
Urgency): Sum
-
Summarized variables:
-
mh_y_upps__nurg_001
-
mh_y_upps__nurg_002
-
mh_y_upps__nurg_003
-
mh_y_upps__nurg_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_upps__nurg_sum(
data,
name = "mh_y_upps__nurg_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_upps__nurg_sum(data) |>
select(
any_of(c("mh_y_upps__nurg_sum", vars_mh_y_upps__nurg))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of Perseverance (GSSF)): Sum"
Description
Computes the summary score mh_y_upps__pers_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Perseverance (GSSF)): Sum
-
Summarized variables:
-
mh_y_upps__pers_001
-
mh_y_upps__pers_002
-
mh_y_upps__pers_003
-
mh_y_upps__pers_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_upps__pers_sum(
data,
name = "mh_y_upps__pers_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_upps__pers_sum(data) |>
select(
any_of(c("mh_y_upps__pers_sum", vars_mh_y_upps__pers))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of Planning): Sum"
Description
Computes the summary score mh_y_upps__plan_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Planning): Sum
-
Summarized variables:
-
mh_y_upps__plan_001
-
mh_y_upps__plan_002
-
mh_y_upps__plan_003
-
mh_y_upps__plan_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_upps__plan_sum(
data,
name = "mh_y_upps__plan_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_upps__plan_sum(data) |>
select(
any_of(c("mh_y_upps__plan_sum", vars_mh_y_upps__plan))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive Urgency): Sum"
Description
Computes the summary score mh_y_upps__purg_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive
Urgency): Sum
-
Summarized variables:
-
mh_y_upps__purg_001
-
mh_y_upps__purg_002
-
mh_y_upps__purg_003
-
mh_y_upps__purg_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_upps__purg_sum(
data,
name = "mh_y_upps__purg_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_upps__purg_sum(data) |>
select(
any_of(c("mh_y_upps__purg_sum", vars_mh_y_upps__purg))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation Seeking): Sum"
Description
Computes the summary score mh_y_upps__sens_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation
Seeking): Sum
-
Summarized variables:
-
mh_y_upps__sens_001
-
mh_y_upps__sens_002
-
mh_y_upps__sens_003
-
mh_y_upps__sens_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
compute_mh_y_upps__sens_sum(
data,
name = "mh_y_upps__sens_sum",
max_na = 0,
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_upps__sens_sum(data) |>
select(
any_of(c("mh_y_upps__sens_sum", vars_mh_y_upps__sens))
)
## End(Not run)
Compute all summary scores for mh_y_upps.
Description
This function computes all summary scores for the mh_y_upps table. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_upps_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_upps_all(data)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Sum"
Description
Computes the summary score mh_y_ysr__dsm__adhd_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Sum
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_ysr__dsm__adhd_sum(
data,
name = "mh_y_ysr__dsm__adhd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__adhd_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__adhd_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__adhd_sum", vars_mh_y_ysr__dsm__adhd))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): T-score"
Description
Computes the summary score mh_y_ysr__dsm__adhd_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): T-score
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_ysr__dsm__adhd_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__adhd_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__adhd_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__adhd_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__adhd_tscore", vars_mh_y_ysr__dsm__adhd))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems): Sum"
Description
Computes the summary score mh_y_ysr__dsm__anx_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
Sum
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_y_ysr__dsm__anx_sum(
data,
name = "mh_y_ysr__dsm__anx_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__anx_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__anx_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__anx_sum", vars_mh_y_ysr__dsm__anx))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems): T-score"
Description
Computes the summary score mh_y_ysr__dsm__anx_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
T-score
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_y_ysr__dsm__anx_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__anx_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__anx_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__anx_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__anx_tscore", vars_mh_y_ysr__dsm__anx))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems): Sum"
Description
Computes the summary score mh_y_ysr__dsm__cond_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
Sum
-
Summarized variables:
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_y_ysr__dsm__cond_sum(
data,
name = "mh_y_ysr__dsm__cond_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__cond_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__cond_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__cond_sum", vars_mh_y_ysr__dsm__cond))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems): T-score"
Description
Computes the summary score mh_y_ysr__dsm__cond_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
T-score
-
Summarized variables:
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_y_ysr__dsm__cond_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__cond_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__cond_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__cond_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__cond_tscore", vars_mh_y_ysr__dsm__cond))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive problems): Sum"
Description
Computes the summary score mh_y_ysr__dsm__dep_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): Sum
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_y_ysr__dsm__dep_sum(
data,
name = "mh_y_ysr__dsm__dep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__dep_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__dep_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__dep_sum", vars_mh_y_ysr__dsm__dep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive problems): T-score"
Description
Computes the summary score mh_y_ysr__dsm__dep_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): T-score
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_y_ysr__dsm__dep_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__dep_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__dep_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__dep_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__dep_tscore", vars_mh_y_ysr__dsm__dep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant problems): Sum"
Description
Computes the summary score mh_y_ysr__dsm__opp_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): Sum
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 5 items missing
Usage
compute_mh_y_ysr__dsm__opp_sum(
data,
name = "mh_y_ysr__dsm__opp_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__opp_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__opp_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__opp_sum", vars_mh_y_ysr__dsm__opp))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant problems): T-score"
Description
Computes the summary score mh_y_ysr__dsm__opp_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): T-score
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 5 items missing
Usage
compute_mh_y_ysr__dsm__opp_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__opp_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__opp_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__opp_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__opp_tscore", vars_mh_y_ysr__dsm__opp))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_y_ysr__dsm__somat_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
Sum
-
Summarized variables:
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_ysr__dsm__somat_sum(
data,
name = "mh_y_ysr__dsm__somat_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__somat_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__somat_sum(data) |>
select(
any_of(c("mh_y_ysr__dsm__somat_sum", vars_mh_y_ysr__dsm__somat))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_y_ysr__dsm__somat_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
T-score
-
Summarized variables:
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 7 items missing
Usage
compute_mh_y_ysr__dsm__somat_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__dsm__somat_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__dsm__somat_nm()
Examples
## Not run:
compute_mh_y_ysr__dsm__somat_tscore(data) |>
select(
any_of(c("mh_y_ysr__dsm__somat_tscore", vars_mh_y_ysr__dsm__somat))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Positive): Sum"
Description
Computes the summary score mh_y_ysr__pos_sum
Youth Self Report [Youth] (Positive): Sum
-
Summarized variables:
-
mh_y_ysr__pos_001
-
mh_y_ysr__pos_002
-
mh_y_ysr__pos_003
-
mh_y_ysr__pos_004
-
mh_y_ysr__pos_005
-
mh_y_ysr__pos_006
-
mh_y_ysr__pos_007
-
mh_y_ysr__pos_008
-
mh_y_ysr__pos_009
-
mh_y_ysr__pos_010
-
mh_y_ysr__pos_011
-
mh_y_ysr__pos_012
-
mh_y_ysr__pos_013
-
mh_y_ysr__pos_014
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_y_ysr__pos_sum(
data,
name = "mh_y_ysr__pos_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_ysr__pos_sum(data) |>
select(
any_of(c("mh_y_ysr__pos_sum", vars_mh_y_ysr__pos))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Positive): T-score"
Description
Computes the summary score mh_y_ysr__pos_tscore
Youth Self Report [Youth] (Positive): T-score
-
Summarized variables:
-
mh_y_ysr__pos_001
-
mh_y_ysr__pos_002
-
mh_y_ysr__pos_003
-
mh_y_ysr__pos_004
-
mh_y_ysr__pos_005
-
mh_y_ysr__pos_006
-
mh_y_ysr__pos_007
-
mh_y_ysr__pos_008
-
mh_y_ysr__pos_009
-
mh_y_ysr__pos_010
-
mh_y_ysr__pos_011
-
mh_y_ysr__pos_012
-
mh_y_ysr__pos_013
-
mh_y_ysr__pos_014
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 14 items missing
Usage
compute_mh_y_ysr__pos_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__pos_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_ysr__pos_tscore(data) |>
select(
any_of(c("mh_y_ysr__pos_tscore", vars_mh_y_ysr__pos))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior): Sum"
Description
Computes the summary score mh_y_ysr__synd__aggr_sum
Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior): Sum
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_y_ysr__synd__aggr_sum(
data,
name = "mh_y_ysr__synd__aggr_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__aggr_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__aggr_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__aggr_sum", vars_mh_y_ysr__synd__aggr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Aggressive): T-score"
Description
Computes the summary score mh_y_ysr__synd__aggr_tscore
Youth Self Report [Youth] (Syndrome Scale - Aggressive): T-score
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 17 items missing
Usage
compute_mh_y_ysr__synd__aggr_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__aggr_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__aggr_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__aggr_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__aggr_tscore", vars_mh_y_ysr__synd__aggr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Sum"
Description
Computes the summary score mh_y_ysr__synd__anxdep_sum
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Sum
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_y_ysr__synd__anxdep_sum(
data,
name = "mh_y_ysr__synd__anxdep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__anxdep_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__anxdep_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__anxdep_sum", vars_mh_y_ysr__synd__anxdep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): T-score"
Description
Computes the summary score mh_y_ysr__synd__anxdep_tscore
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed):
T-score
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 13 items missing
Usage
compute_mh_y_ysr__synd__anxdep_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__anxdep_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__anxdep_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__anxdep_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__anxdep_tscore", vars_mh_y_ysr__synd__anxdep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Attention problems): Sum"
Description
Computes the summary score mh_y_ysr__synd__attn_sum
Youth Self Report [Youth] (Syndrome Scale - Attention problems): Sum
-
Summarized variables:
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn_004
-
mh_y_ysr__attn__adhd_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_y_ysr__synd__attn_sum(
data,
name = "mh_y_ysr__synd__attn_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__attn_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__attn_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__attn_sum", vars_mh_y_ysr__synd__attn))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Attention problems): T-score"
Description
Computes the summary score mh_y_ysr__synd__attn_tscore
Youth Self Report [Youth] (Syndrome Scale - Attention problems):
T-score
-
Summarized variables:
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn_004
-
mh_y_ysr__attn__adhd_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 9 items missing
Usage
compute_mh_y_ysr__synd__attn_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__attn_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__attn_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__attn_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__attn_tscore", vars_mh_y_ysr__synd__attn))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - External): Sum"
Description
Computes the summary score mh_y_ysr__synd__ext_sum
Youth Self Report [Youth] (Syndrome Scale - External): Sum
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_y_ysr__synd__ext_sum(
data,
name = "mh_y_ysr__synd__ext_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__ext_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__ext_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__ext_sum", vars_mh_y_ysr__synd__ext))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - External): T-score"
Description
Computes the summary score mh_y_ysr__synd__ext_tscore
Youth Self Report [Youth] (Syndrome Scale - External): T-score
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 32 items missing
Usage
compute_mh_y_ysr__synd__ext_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__ext_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__ext_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__ext_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__ext_tscore", vars_mh_y_ysr__synd__ext))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Internaling): Sum"
Description
Computes the summary score mh_y_ysr__synd__int_sum
Youth Self Report [Youth] (Syndrome Scale - Internaling): Sum
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 31 items missing
Usage
compute_mh_y_ysr__synd__int_sum(
data,
name = "mh_y_ysr__synd__int_sum",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__int_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__int_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__int_sum", vars_mh_y_ysr__synd__int))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Internaling): T-score"
Description
Computes the summary score mh_y_ysr__synd__int_tscore
Youth Self Report [Youth] (Syndrome Scale - Internaling): T-score
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 2 of 31 items missing
Usage
compute_mh_y_ysr__synd__int_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__int_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 2,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__int_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__int_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__int_tscore", vars_mh_y_ysr__synd__int))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Other problems): Sum"
Description
Computes the summary score mh_y_ysr__synd__othpr_sum
Youth Self Report [Youth] (Other problems): Sum
-
Summarized variables:
-
mh_y_ysr__othpr_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__othpr_002
-
mh_y_ysr__othpr_003
-
mh_y_ysr__othpr_004
-
mh_y_ysr__othpr_005
-
mh_y_ysr__othpr_006
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__othpr_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_y_ysr__synd__othpr_sum(
data,
name = "mh_y_ysr__synd__othpr_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__othpr_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__othpr_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__othpr_sum", vars_mh_y_ysr__synd__othpr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior): Sum"
Description
Computes the summary score mh_y_ysr__synd__rule_sum
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
Sum
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_y_ysr__synd__rule_sum(
data,
name = "mh_y_ysr__synd__rule_sum",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__rule_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__rule_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__rule_sum", vars_mh_y_ysr__synd__rule))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior): T-score"
Description
Computes the summary score mh_y_ysr__synd__rule_tscore
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
T-score
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 of 15 items missing
Usage
compute_mh_y_ysr__synd__rule_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__rule_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 1,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__rule_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__rule_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__rule_tscore", vars_mh_y_ysr__synd__rule))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale -Social problems): Sum"
Description
Computes the summary score mh_y_ysr__synd__soc_sum
Youth Self Report [Youth] (Syndrome Scale -Social problems): Sum
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_y_ysr__synd__soc_sum(
data,
name = "mh_y_ysr__synd__soc_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__soc_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__soc_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__soc_sum", vars_mh_y_ysr__synd__soc))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale -Social): T-score"
Description
Computes the summary score mh_y_ysr__synd__soc_tscore
Youth Self Report [Youth] (Syndrome Scale -Social): T-score
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 11 items missing
Usage
compute_mh_y_ysr__synd__soc_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__soc_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__soc_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__soc_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__soc_tscore", vars_mh_y_ysr__synd__soc))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Somatic complaints): Sum"
Description
Computes the summary score mh_y_ysr__synd__som_sum
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints): Sum
-
Summarized variables:
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_y_ysr__synd__som_sum(
data,
name = "mh_y_ysr__synd__som_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__som_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__som_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__som_sum", vars_mh_y_ysr__synd__som))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Somatic complaints): T-score"
Description
Computes the summary score mh_y_ysr__synd__som_tscore
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints):
T-score
-
Summarized variables:
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 10 items missing
Usage
compute_mh_y_ysr__synd__som_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__som_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__som_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__som_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__som_tscore", vars_mh_y_ysr__synd__som))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Thought problems): Sum"
Description
Computes the summary score mh_y_ysr__synd__tho_sum
Youth Self Report [Youth] (Syndrome Scale - Thought problems): Sum
-
Summarized variables:
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
mh_y_ysr__tho__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 12 items missing
Usage
compute_mh_y_ysr__synd__tho_sum(
data,
name = "mh_y_ysr__synd__tho_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__tho_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__tho_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__tho_sum", vars_mh_y_ysr__synd__tho))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Thought problems): T-score"
Description
Computes the summary score mh_y_ysr__synd__tho_tscore
Youth Self Report [Youth] (Syndrome Scale - Thought problems): T-score
-
Summarized variables:
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
mh_y_ysr__tho__dep_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 12 items missing
Usage
compute_mh_y_ysr__synd__tho_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__tho_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__tho_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__tho_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__tho_tscore", vars_mh_y_ysr__synd__tho))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed): Sum"
Description
Computes the summary score mh_y_ysr__synd__wthdep_sum
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed): Sum
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_y_ysr__synd__wthdep_sum(
data,
name = "mh_y_ysr__synd__wthdep_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__wthdep_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__wthdep_sum(data) |>
select(
any_of(c("mh_y_ysr__synd__wthdep_sum", vars_mh_y_ysr__synd__wthdep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed): T-score"
Description
Computes the summary score mh_y_ysr__synd__wthdep_tscore
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed):
T-score
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 8 items missing
Usage
compute_mh_y_ysr__synd__wthdep_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr__synd__wthdep_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
compute_mh_y_ysr__synd__wthdep_nm()
Examples
## Not run:
compute_mh_y_ysr__synd__wthdep_tscore(data) |>
select(
any_of(c("mh_y_ysr__synd__wthdep_tscore", vars_mh_y_ysr__synd__wthdep))
)
## End(Not run)
Compute all summary scores for mh_y_ysr.
Description
This function computes all summary scores for the mh_y_ysr form. Make sure to have all necessary columns in the data frame.
Usage
compute_mh_y_ysr_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_mh_y_ysr_all(data)
## End(Not run)
Compute "Youth Self Report [Youth]: Sum"
Description
Computes the summary score mh_y_ysr_sum
Youth Self Report [Youth]: Sum
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn_004
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule_005
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som_001
-
mh_y_ysr__othpr_001
-
mh_y_ysr__othpr_002
-
mh_y_ysr__othpr_003
-
mh_y_ysr__othpr_004
-
mh_y_ysr__othpr_005
-
mh_y_ysr__othpr_006
-
mh_y_ysr__othpr_007
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 7 of 105 items missing
Usage
compute_mh_y_ysr_sum(
data,
name = "mh_y_ysr_sum",
max_na = 7,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_ysr_sum(data) |>
select(
any_of(c("mh_y_ysr_sum", vars_mh_y_ysr))
)
## End(Not run)
Compute "Youth Self Report [Youth]: T-score"
Description
Computes the summary score mh_y_ysr_tscore
Youth Self Report [Youth]: T-score
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn_004
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule_005
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som_001
-
mh_y_ysr__othpr_001
-
mh_y_ysr__othpr_002
-
mh_y_ysr__othpr_003
-
mh_y_ysr__othpr_004
-
mh_y_ysr__othpr_005
-
mh_y_ysr__othpr_006
-
mh_y_ysr__othpr_007
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
-
Excluded values:
777
999
-
Validation criterion: maximally 7 of 105 items missing
Usage
compute_mh_y_ysr_tscore(
data,
data_norm = NULL,
name = "mh_y_ysr_tscore",
col_age = "mh_y_ysr_age",
col_sex = "ab_g_stc__cohort_sex",
max_na = 7,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
See Also
Examples
## Not run:
compute_mh_y_ysr_tscore(data) |>
select(
any_of(c("mh_y_ysr_tscore", vars_mh_y_ysr))
)
## End(Not run)
Compute "Barkley Deficits in Executive Functioning Scale [Parent] (EF Symptom Count, number of answers of 3 or 4): Count"
Description
Computes the summary score nc_p_bdefs__sympt_count
Barkley Deficits in Executive Functioning Scale [Parent] (EF Symptom
Count, number of answers of 3 or 4): Count
-
Summarized variables:
-
nc_p_bdefs_001
-
nc_p_bdefs_002
-
nc_p_bdefs_003
-
nc_p_bdefs_004
-
nc_p_bdefs_005
-
nc_p_bdefs_006
-
nc_p_bdefs_007
-
nc_p_bdefs_008
-
nc_p_bdefs_009
-
nc_p_bdefs_010
-
nc_p_bdefs_011
-
nc_p_bdefs_012
-
nc_p_bdefs_013
-
nc_p_bdefs_014
-
nc_p_bdefs_015
-
nc_p_bdefs_016
-
nc_p_bdefs_017
-
nc_p_bdefs_018
-
nc_p_bdefs_019
-
nc_p_bdefs_020
-
Usage
compute_nc_p_bdefs__sympt_count(
data,
name = "nc_p_bdefs__sympt_count",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_nc_p_bdefs__sympt_count(data) |>
select(
data,
all_of(c("nc_p_bdefs__sympt_count", vars_nc_p_bdefs))
)
## End(Not run)
Compute all the BDEFS summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_nc_p_bdefs_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_nc_p_bdefs_all(data)
## End(Not run)
Compute "Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary Score): Number missing"
Description
Computes the summary score nc_p_bdefs_nm
Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary
Score): Number missing
-
Summarized variables:
-
nc_p_bdefs_001
-
nc_p_bdefs_002
-
nc_p_bdefs_003
-
nc_p_bdefs_004
-
nc_p_bdefs_005
-
nc_p_bdefs_006
-
nc_p_bdefs_007
-
nc_p_bdefs_008
-
nc_p_bdefs_009
-
nc_p_bdefs_010
-
nc_p_bdefs_011
-
nc_p_bdefs_012
-
nc_p_bdefs_013
-
nc_p_bdefs_014
-
nc_p_bdefs_015
-
nc_p_bdefs_016
-
nc_p_bdefs_017
-
nc_p_bdefs_018
-
nc_p_bdefs_019
-
nc_p_bdefs_020
-
Usage
compute_nc_p_bdefs_nm(data, name = "nc_p_bdefs_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_nc_p_bdefs_nm(data) |>
select(
data,
all_of(c("nc_p_bdefs_nm", vars_nc_p_bdefs))
)
## End(Not run)
Compute all the EHIS summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_nc_y_ehis_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_nc_y_ehis_all(data)
## End(Not run)
Compute "Edinburgh Handedness Inventory [Youth]: Number missing"
Description
Computes the summary score nc_y_ehis_nm
Edinburgh Handedness Inventory [Youth]: Number missing
-
Summarized variables:
-
nc_y_ehis_001
-
nc_y_ehis_002
-
nc_y_ehis_003
-
nc_y_ehis_004
-
Usage
compute_nc_y_ehis_nm(data, name = "nc_y_ehis_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_nc_y_ehis_nm(data) |>
select(
data,
all_of(c("nc_y_ehis_nm", vars_nc_y_ehis))
)
## End(Not run)
Compute "Youth Screen Time [Parent] (Problematic Media Use): Number missing"
Description
Computes the summary score nt_p_yst__pmum_nm
Youth Screen Time [Parent] (Problematic Media Use): Number missing
-
Summarized variables:
-
nt_p_yst__pmum_001
-
nt_p_yst__pmum_002
-
nt_p_yst__pmum_003
-
nt_p_yst__pmum_004
-
nt_p_yst__pmum_005
-
nt_p_yst__pmum_006
-
nt_p_yst__pmum_007
-
nt_p_yst__pmum_008
-
nt_p_yst__pmum_009
-
-
Excluded values:
777
999
Usage
compute_nt_p_yst__pmum_nm(data, name = "nt_p_yst__pmum_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Youth Screen Time [Parent] (Weekday): Number missing"
Description
Computes the summary score nt_p_yst__screen__wkdy_nm
Youth Screen Time [Parent] (Weekday): Number missing
-
Summarized variables:
-
nt_p_yst__wkdy__hr_001
-
nt_p_yst__wkdy__min_001
-
nt_p_yst__wkdy__min_001__v01
-
-
Excluded values:
777
999
Usage
compute_nt_p_yst__screen__wkdy_nm(
data,
name = "nt_p_yst__screen__wkdy_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Youth Screen Time [Parent] (Weekend): Number missing"
Description
Computes the summary score nt_p_yst__screen__wknd_nm
Youth Screen Time [Parent] (Weekend): Number missing
-
Summarized variables:
-
nt_p_yst__wknd__hr_001
-
nt_p_yst__wknd__min_001
-
nt_p_yst__wknd__min_001__v01
-
-
Excluded values:
777
999
Usage
compute_nt_p_yst__screen__wknd_nm(
data,
name = "nt_p_yst__screen__wknd_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for nt_p_yst.
Description
This function computes all summary scores for the nt_p_yst form. Make sure to have all necessary columns in the data frame.
Usage
compute_nt_p_yst_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_nt_p_yst_all(data)
## End(Not run)
Compute "Screen Time [Youth] (Weekday): Number missing"
Description
Computes the summary score nt_y_stq__screen__wkdy_nm
Screen Time [Youth] (Weekday): Number missing
-
Summarized variables:
-
nt_y_stq__screen__wkdy_001
-
nt_y_stq__screen__wkdy_002
-
nt_y_stq__screen__wkdy_003
-
nt_y_stq__screen__wkdy_004
-
nt_y_stq__screen__wkdy_005
-
nt_y_stq__screen__wkdy_006
-
nt_y_stq__screen__wkdy__hr_001
-
nt_y_stq__screen__wkdy__min_001
-
nt_y_stq__screen__wkdy__hr_001__v01
-
nt_y_stq__screen__wkdy__min_001__v01
-
nt_y_stq__screen__wkdy__hr_002
-
nt_y_stq__screen__wkdy__min_002
-
nt_y_stq__screen__wkdy__hr_003
-
nt_y_stq__screen__wkdy__min_003
-
nt_y_stq__screen__wkdy__hr_004
-
nt_y_stq__screen__wkdy__min_004
-
nt_y_stq__screen__wkdy__hr_005
-
nt_y_stq__screen__wkdy__min_005
-
nt_y_stq__screen__wkdy__hr_006
-
nt_y_stq__screen__wkdy__min_006
-
nt_y_stq__screen__wkdy__hr_007
-
nt_y_stq__screen__wkdy__min_007
-
nt_y_stq__screen__wkdy__hr_008
-
nt_y_stq__screen__wkdy__min_008
-
nt_y_stq__screen__wkdy__hr_009
-
nt_y_stq__screen__wkdy__min_009
-
-
Excluded values:
777
999
Usage
compute_nt_y_stq__screen__wkdy_nm(
data,
name = "nt_y_stq__screen__wkdy_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Screen Time [Youth] (Weekend): Number missing"
Description
Computes the summary score nt_y_stq__screen__wknd_nm
Screen Time [Youth] (Weekend): Number missing
-
Summarized variables:
-
nt_y_stq__screen__wknd_001
-
nt_y_stq__screen__wknd_002
-
nt_y_stq__screen__wknd_003
-
nt_y_stq__screen__wknd_004
-
nt_y_stq__screen__wknd_005
-
nt_y_stq__screen__wknd_006
-
nt_y_stq__screen__wknd__hr_001
-
nt_y_stq__screen__wknd__min_001
-
nt_y_stq__screen__wknd__hr_001__v01
-
nt_y_stq__screen__wknd__min_001__v01
-
nt_y_stq__screen__wknd__hr_002
-
nt_y_stq__screen__wknd__min_002
-
nt_y_stq__screen__wknd__hr_003
-
nt_y_stq__screen__wknd__min_003
-
nt_y_stq__screen__wknd__hr_004
-
nt_y_stq__screen__wknd__min_004
-
nt_y_stq__screen__wknd__hr_005
-
nt_y_stq__screen__wknd__min_005
-
nt_y_stq__screen__wknd__hr_006
-
nt_y_stq__screen__wknd__min_006
-
nt_y_stq__screen__wknd__hr_007
-
nt_y_stq__screen__wknd__min_007
-
nt_y_stq__screen__wknd__hr_008
-
nt_y_stq__screen__wknd__min_008
-
nt_y_stq__screen__wknd__hr_009
-
nt_y_stq__screen__wknd__min_009
-
-
Excluded values:
777
999
Usage
compute_nt_y_stq__screen__wknd_nm(
data,
name = "nt_y_stq__screen__wknd_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for nt_y_stq
Description
This function computes all summary scores for the nt_y_stq form. Make sure to have all necessary columns in the data frame.
Usage
compute_nt_y_stq_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_nt_y_stq_all(data)
## End(Not run)
Compute all the ph_p_cna
summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_p_cna_all(data)
Arguments
data |
tbl. Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_p_cna(data)
## End(Not run)
Compute "Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_cna_sum
Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_p_cna_001
-
ph_p_cna_002
-
ph_p_cna_003
-
ph_p_cna_004
-
ph_p_cna_005
-
ph_p_cna_006
-
ph_p_cna_007
-
ph_p_cna_008
-
ph_p_cna_009
-
ph_p_cna_010
-
ph_p_cna_011
-
ph_p_cna_012
-
ph_p_cna_013
-
ph_p_cna_014
-
-
Excluded values:
999
777
Usage
compute_ph_p_cna_nm(
data,
name = "ph_p_cna_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_p_cna_nm(data) |>
select(
all_of(c("ph_p_cna_nm", vars_ph_p_cna))
)
## End(Not run)
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness - Over 30 minutes): Number missing"
Description
Computes the summary score ph_p_otbi__loc__30m_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness - Over 30 minutes): Number missing
-
Excluded values:
777
999
Usage
compute_ph_p_otbi__loc__30m_nm(
data,
name = "ph_p_otbi__loc__30m_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_p_otbi__loc__30m_count()
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness): Age of first injury with LOC - Number missing"
Description
Computes the summary score ph_p_otbi__loc__tbiage_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Age of first injury with LOC - Number missing
-
Excluded values:
777
999
-
Notes:
The output is set to
NA
when no head or neck injury/impact is reported
Usage
compute_ph_p_otbi__loc__tbiage_nm(
data,
name = "ph_p_otbi__loc__tbiage_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_p_otbi__loc_tbiage()
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness): Number missing"
Description
Computes the summary score ph_p_otbi__loc_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Number missing
-
Excluded values:
777
999
Usage
compute_ph_p_otbi__loc_nm(
data,
name = "ph_p_otbi__loc_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_p_otbi__loc_count()
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries): Number missing"
Description
Computes the summary score ph_p_otbi__rpt_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries):
Number missing
-
Excluded values:
777
999
Usage
compute_ph_p_otbi__rpt_nm(
data,
name = "ph_p_otbi__rpt_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_p_otbi__rpt_count()
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Moderate TBI"
Description
Computes the summary score ph_p_otbi__tbi4
Ohio State Traumatic Brain Injury Screen [Parent]: Moderate TBI
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__02
-
ph_p_otbi__loc__add_001__03
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__02__l
-
ph_p_otbi__loc__add_001__03__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
-
Excluded values:
777
999
Usage
compute_ph_p_otbi__tbi4(
data,
name = "ph_p_otbi__tbi4",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Severe TBI"
Description
Computes the summary score ph_p_otbi__tbi5
Ohio State Traumatic Brain Injury Screen [Parent]: Severe TBI
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__02
-
ph_p_otbi__loc__add_001__03
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__02__l
-
ph_p_otbi__loc__add_001__03__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
-
Excluded values:
777
999
Usage
compute_ph_p_otbi__tbi5(
data,
name = "ph_p_otbi__tbi5",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the ph_p_otbi scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_ph_p_otbi_all(data)
Arguments
data |
tbl. Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_p_otbi_all(data)
## End(Not run)
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Female): Approximate tanner stages - Number missing"
Description
Computes the summary score ph_p_pds__f__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Approximate tanner stages - Number missing
-
Summarized variables:
-
ph_p_pds_002
-
ph_p_pds__f_001
-
ph_p_pds__f_002
-
-
Excluded values:
777
999
Usage
compute_ph_p_pds__f__categ_nm(
data,
name = "ph_p_pds__f__categ_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Female): Number missing"
Description
Computes the summary score ph_p_pds__f_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Number missing
-
Summarized variables:
-
ph_p_pds_001
-
ph_p_pds_002
-
ph_p_pds_003
-
ph_p_pds__f_001
-
ph_p_pds__f_002
-
-
Excluded values:
777
999
Usage
compute_ph_p_pds__f_nm(
data,
name = "ph_p_pds__f_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Male): Approximate tanner stages - Number missing"
Description
Computes the summary score ph_p_pds__m__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Approximate tanner stages - Number missing
-
Summarized variables:
-
ph_p_pds_002
-
ph_p_pds__m_001
-
ph_p_pds__m_002
-
-
Excluded values:
777
999
Usage
compute_ph_p_pds__m__categ_nm(
data,
name = "ph_p_pds__m__categ_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Male): Number missing"
Description
Computes the summary score ph_p_pds__m_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Number missing
-
Summarized variables:
-
ph_p_pds_001
-
ph_p_pds_002
-
ph_p_pds_003
-
ph_p_pds__m_001
-
ph_p_pds__m_002
-
-
Excluded values:
777
999
Usage
compute_ph_p_pds__m_nm(
data,
name = "ph_p_pds__m_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the ph_p_pds
summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_p_pds_all(data)
Arguments
data |
tbl. Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_p_pds_all(data)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Disorder of arousal) - Number missing"
Description
Computes the summary score ph_p_sds__da_nm
Sleep Disturbance Scale [Parent] (Disorder of arousal) - Number missing
-
Summarized variables:
-
ph_p_sds__da_001
-
ph_p_sds__da_002
-
ph_p_sds__da_003
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__da_nm(
data,
name = "ph_p_sds__da_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining sleep) - Number missing"
Description
Computes the summary score ph_p_sds__dims_nm
Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining
sleep) - Number missing
-
Summarized variables:
-
ph_p_sds__dims_001
-
ph_p_sds__dims_002
-
ph_p_sds__dims_003
-
ph_p_sds__dims_004
-
ph_p_sds__dims_005
-
ph_p_sds__dims_006
-
ph_p_sds__dims_007
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__dims_nm(
data,
name = "ph_p_sds__dims_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence) - Number missing"
Description
Computes the summary score ph_p_sds__does_nm
Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence) -
Number missing
-
Summarized variables:
-
ph_p_sds__does_001
-
ph_p_sds__does_002
-
ph_p_sds__does_003
-
ph_p_sds__does_004
-
ph_p_sds__does_005
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__does_nm(
data,
name = "ph_p_sds__does_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis) - Number missing"
Description
Computes the summary score ph_p_sds__hyphy_nm
Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis) - Number missing
-
Summarized variables:
-
ph_p_sds__hyphy_001
-
ph_p_sds__hyphy_002
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__hyphy_nm(
data,
name = "ph_p_sds__hyphy_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Sleep Disturbance Scale [Parent] (Sleep breathing disorders) - Number missing"
Description
Computes the summary score ph_p_sds__sbd_nm
Sleep Disturbance Scale [Parent] (Sleep breathing disorders) - Number missing
-
Summarized variables:
-
ph_p_sds__sbd_001
-
ph_p_sds__sbd_002
-
ph_p_sds__sbd_003
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__sbd_nm(
data,
name = "ph_p_sds__sbd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders) - Number missing"
Description
Computes the summary score ph_p_sds__swtd_nm
Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders) - Number
missing
-
Summarized variables:
-
ph_p_sds__swtd_001
-
ph_p_sds__swtd_002
-
ph_p_sds__swtd_003
-
ph_p_sds__swtd_004
-
ph_p_sds__swtd_005
-
ph_p_sds__swtd_006
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds__swtd_nm(
data,
name = "ph_p_sds__swtd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the ph_p_sds
summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_p_sds_all(data)
Arguments
data |
tbl. Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_p_sds_all(data)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Total) - Number missing"
Description
Computes the summary score ph_p_sds_nm
Sleep Disturbance Scale [Parent] (Total) - Number missing
-
Summarized variables:
-
ph_p_sds__dims_001
-
ph_p_sds__dims_002
-
ph_p_sds__dims_003
-
ph_p_sds__dims_004
-
ph_p_sds__dims_005
-
ph_p_sds__swtd_001
-
ph_p_sds__swtd_002
-
ph_p_sds__swtd_003
-
ph_p_sds__hyphy_001
-
ph_p_sds__dims_006
-
ph_p_sds__dims_007
-
ph_p_sds__swtd_004
-
ph_p_sds__sbd_001
-
ph_p_sds__sbd_002
-
ph_p_sds__sbd_003
-
ph_p_sds__hyphy_002
-
ph_p_sds__da_001
-
ph_p_sds__swtd_005
-
ph_p_sds__swtd_006
-
ph_p_sds__da_002
-
ph_p_sds__da_003
-
ph_p_sds__does_001
-
ph_p_sds__does_002
-
ph_p_sds__does_003
-
ph_p_sds__does_004
-
ph_p_sds__does_005
-
-
Excluded values:
777
999
Usage
compute_ph_p_sds_nm(
data,
name = "ph_p_sds_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Anthropometrics [Youth] (Height): Number missing"
Description
Computes the summary score ph_y_anthr__height_nm
Anthropometrics [Youth] (Height): Number missing
-
Summarized variables:
-
ph_y_anthr__height__r01_001
-
ph_y_anthr__height__r02_001
-
ph_y_anthr__height__r03_001
-
-
Excluded values: none
Usage
compute_ph_y_anthr__height_nm(
data,
name = "ph_y_anthr__height_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_y_anthr__height_mean()
Examples
## Not run:
compute_ph_y_anthr__height_nm(data) |>
select(
all_of(c("ph_y_anthr__height_nm", vars_ph_y_anthr__height))
)
## End(Not run)
Compute "Anthropometrics [Youth] (Weight): Number missing"
Description
Computes the summary score ph_y_anthr__weight_nm
Anthropometrics [Youth] (Weight): Number missing
-
Summarized variables:
-
ph_y_anthr__weight__r01_001
-
ph_y_anthr__weight__r02_001
-
ph_y_anthr__weight__r03_001
-
-
Excluded values: none
Usage
compute_ph_y_anthr__weight_nm(
data,
name = "ph_y_anthr__weight_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_y_anthr__weight_mean()
Examples
## Not run:
compute_ph_y_anthr__weight_nm(data) |>
select(
all_of(c("ph_y_anthr__weight_nm", vars_ph_y_anthr__weight))
)
## End(Not run)
Compute all the youth anthropometric measurements.
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_y_anthr_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_y_anthr_all(data)
## End(Not run)
Compute "Blood Pressure [Youth] (Diastolic): Number missing"
Description
Computes the summary score ph_y_bp__dia_nm
Blood Pressure [Youth] (Diastolic): Number missing
-
Summarized variables:
-
ph_y_bp__dia__r01_001
-
ph_y_bp__dia__r01_002
-
ph_y_bp__dia__r01_003
-
ph_y_bp__dia__r02_001
-
ph_y_bp__dia__r02_002
-
ph_y_bp__dia__r03_001
-
ph_y_bp__dia__r03_002
-
-
Excluded values: none
Calculation
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
Usage
compute_ph_y_bp__dia_nm(data, name = "ph_y_bp__dia_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_ph_y_bp__dia_nm(data) |>
select(
all_of(c("ph_y_bp__dia_nm", vars_ph_y_bp__dia))
)
## End(Not run)
Compute "Blood Pressure [Youth] (Heart rate): Number missing"
Description
Computes the summary score ph_y_bp__hrate_nm
Blood Pressure [Youth] (Heart rate): Number missing
-
Summarized variables:
-
ph_y_bp__hrate__r01_001
-
ph_y_bp__hrate__r01_002
-
ph_y_bp__hrate__r01_003
-
ph_y_bp__hrate__r02_001
-
ph_y_bp__hrate__r02_002
-
ph_y_bp__hrate__r03_001
-
ph_y_bp__hrate__r03_002
-
-
Excluded values: none
Calculation
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
Usage
compute_ph_y_bp__hrate_nm(data, name = "ph_y_bp__hrate_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_ph_y_bp__hrate_nm(data) |>
select(
all_of(c("ph_y_bp__hrate_nm", vars_ph_y_bp__hrate))
)
## End(Not run)
Compute "Blood Pressure [Youth] (Systolic): Number missing"
Description
Computes the summary score ph_y_bp__sys_nm
Blood Pressure [Youth] (Systolic): Number missing
-
Summarized variables:
-
ph_y_bp__sys__r01_001
-
ph_y_bp__sys__r01_002
-
ph_y_bp__sys__r01_003
-
ph_y_bp__sys__r02_001
-
ph_y_bp__sys__r02_002
-
ph_y_bp__sys__r03_001
-
ph_y_bp__sys__r03_002
-
-
Excluded values: none
Calculation
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
Usage
compute_ph_y_bp__sys_nm(data, name = "ph_y_bp__sys_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_ph_y_bp__sys_nm(data) |>
select(
all_of(c("ph_y_bp__sys_nm", vars_ph_y_bp__sys))
)
## End(Not run)
Compute all the youth blood pressure measurements.
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_y_bp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_y_bp_all(data)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__bed__end__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__end__24h_t
(intermediate score) -
ph_y_mctq__fd__sleep_inertia
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__bed__end__24h_t(
data,
name = "ph_y_mctq__fd__bed__end__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__bed__end__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__bed__end__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__bed__end__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep_inertia
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__bed__end__36h_t(
data,
name = "ph_y_mctq__fd__bed__end__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__bed__end__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__bed__end__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - In bed start): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__bed__start__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed start):
Time [24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_001__02
-
ph_y_mctq__fd_001__01a
-
ph_y_mctq__fd_001__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__bed__start__24h_t(
data,
name = "ph_y_mctq__fd__bed__start__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__bed__start__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_001__02",
"ph_y_mctq__fd_001__01a",
"ph_y_mctq__fd_001__01b",
"ph_y_mctq__fd__bed__start__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - In bed start): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__bed__start__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed start):
Time [36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_001__02
-
ph_y_mctq__fd_001__01a
-
ph_y_mctq__fd_001__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__bed__start__36h_t(
data,
name = "ph_y_mctq__fd__bed__start__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__bed__start__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_001__02",
"ph_y_mctq__fd_001__01a",
"ph_y_mctq__fd_001__01b",
"ph_y_mctq__fd__bed__start__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - In bed): Sum"
Description
Computes the summary score ph_y_mctq__fd__bed_sum
Munich Chronotype Questionnaire [Youth] (Free Day - In bed): Sum
-
Summarized variables:
-
ph_y_mctq__fd__bed__end__36h_t
(intermediate score) -
ph_y_mctq__fd__bed__start__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__bed_sum(
data,
name = "ph_y_mctq__fd__bed_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__bed_sum(data) |>
select(
any_of(c(
"ph_y_mctq__fd__bed_sum"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__end__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_005__02
-
ph_y_mctq__fd_005__01a
-
ph_y_mctq__fd_005__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__end__24h_t(
data,
name = "ph_y_mctq__fd__sleep__end__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep__end__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_005__02",
"ph_y_mctq__fd_005__01a",
"ph_y_mctq__fd_005__01b",
"ph_y_mctq__fd__sleep__end__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__end__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_005__02
-
ph_y_mctq__fd_005__01a
-
ph_y_mctq__fd_005__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__end__36h_t(
data,
name = "ph_y_mctq__fd__sleep__end__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep__end__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_005__02",
"ph_y_mctq__fd_005__01a",
"ph_y_mctq__fd_005__01b",
"ph_y_mctq__fd__sleep__end__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__mid__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__onset__24h_t
(intermediate score) -
ph_y_mctq__fd__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__mid__24h_t(
data,
name = "ph_y_mctq__fd__sleep__mid__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep__mid__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep__mid__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__mid__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep_period
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__mid__36h_t(
data,
name = "ph_y_mctq__fd__sleep__mid__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep__mid__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep__mid__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__onset__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__start__24h_t
(intermediate score) -
ph_y_mctq__fd__sleep_latent
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__onset__24h_t(
data,
name = "ph_y_mctq__fd__sleep__onset__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep__onset__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep__onset__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__onset__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep__start__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep_latent
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__onset__36h_t(
data,
name = "ph_y_mctq__fd__sleep__onset__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep__onset__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep__onset__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__start__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_002__02
-
ph_y_mctq__fd_002__01a
-
ph_y_mctq__fd_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__start__24h_t(
data,
name = "ph_y_mctq__fd__sleep__start__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep__start__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_002__02",
"ph_y_mctq__fd_002__01a",
"ph_y_mctq__fd_002__01b",
"ph_y_mctq__fd__sleep__start__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__fd__sleep__start__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd_002__02
-
ph_y_mctq__fd_002__01a
-
ph_y_mctq__fd_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__start__36h_t(
data,
name = "ph_y_mctq__fd__sleep__start__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep__start__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_002__02",
"ph_y_mctq__fd_002__01a",
"ph_y_mctq__fd_002__01b",
"ph_y_mctq__fd__sleep__start__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep wakenings after sleep onset): Sum"
Description
Computes the summary score ph_y_mctq__fd__sleep__waso_sum
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep wakenings
after sleep onset): Sum
-
Summarized variables:
-
ph_y_mctq__fd_004
-
ph_y_mctq__fd_004__01
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep__waso_sum(
data,
name = "ph_y_mctq__fd__sleep__waso_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep__waso_sum(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_004",
"ph_y_mctq__fd_004__01",
"ph_y_mctq__fd__sleep__waso_sum"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Duration"
Description
Computes the summary score ph_y_mctq__fd__sleep_dur
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Duration
-
Summarized variables:
-
ph_y_mctq__fd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__waso_sum
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep_dur(
data,
name = "ph_y_mctq__fd__sleep_dur",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep_dur(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep_dur"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Inertia"
Description
Computes the summary score ph_y_mctq__fd__sleep_inertia
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Inertia
-
Summarized variables:
-
ph_y_mctq__fd_006
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep_inertia(
data,
name = "ph_y_mctq__fd__sleep_inertia",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep_inertia(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_006",
"ph_y_mctq__fd__sleep_inertia"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Latency"
Description
Computes the summary score ph_y_mctq__fd__sleep_latent
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Latency
-
Summarized variables:
-
ph_y_mctq__fd_003
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep_latent(
data,
name = "ph_y_mctq__fd__sleep_latent",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__fd__sleep_latent(data)
select(
data,
any_of(c(
"ph_y_mctq__fd_003",
"ph_y_mctq__fd__sleep_latent"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Period"
Description
Computes the summary score ph_y_mctq__fd__sleep_period
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Period
-
Summarized variables:
-
ph_y_mctq__fd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd__sleep_period(
data,
name = "ph_y_mctq__fd__sleep_period",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd__sleep_period(data) |>
select(
any_of(c(
"ph_y_mctq__fd__sleep_period"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Free Day): Count"
Description
Computes the summary score ph_y_mctq__fd_count
Munich Chronotype Questionnaire [Youth] (Free Day): Count
-
Summarized variables:
-
ph_y_mctq__sd_count
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__fd_count(data, name = "ph_y_mctq__fd_count", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__fd_count(data) |>
select(
any_of(c(
"ph_y_mctq__fd_count"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Raw: Chronotype): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__raw__36h_chrono
Munich Chronotype Questionnaire [Youth] (Raw: Chronotype): Time [36
hour adjusted]
-
Summarized variables:
-
ph_y_mctq__fd__sleep_dur
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score) -
ph_y_mctq__fd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__raw__36h_chrono(
data,
name = "ph_y_mctq__raw__36h_chrono",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__raw__36h_chrono(data) |>
select(
any_of(c(
"ph_y_mctq__raw__36h_chrono"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__school__leave__24h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__school_003__02
-
ph_y_mctq__school_003__01a
-
ph_y_mctq__school_003__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__school__leave__24h_t(
data,
name = "ph_y_mctq__school__leave__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__school__leave__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__school_003__02",
"ph_y_mctq__school_003__01a",
"ph_y_mctq__school_003__01b",
"ph_y_mctq__school__leave__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__school__leave__36h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__school_003__02
-
ph_y_mctq__school_003__01a
-
ph_y_mctq__school_003__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__school__leave__36h_t(
data,
name = "ph_y_mctq__school__leave__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__school__leave__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__school_003__02",
"ph_y_mctq__school_003__01a",
"ph_y_mctq__school_003__01b",
"ph_y_mctq__school__leave__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__school__start__24h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__school_002__02
-
ph_y_mctq__school_002__01a
-
ph_y_mctq__school_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__school__start__24h_t(
data,
name = "ph_y_mctq__school__start__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__school__start__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__school_002__02",
"ph_y_mctq__school_002__01a",
"ph_y_mctq__school_002__01b",
"ph_y_mctq__school__start__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__school__start__36h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__school_002__02
-
ph_y_mctq__school_002__01a
-
ph_y_mctq__school_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__school__start__36h_t(
data,
name = "ph_y_mctq__school__start__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__school__start__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__school_002__02",
"ph_y_mctq__school_002__01a",
"ph_y_mctq__school_002__01b",
"ph_y_mctq__school__start__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - In bed end): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__bed__end__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed end):
Time [24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__end__24h_t
(intermediate score) -
ph_y_mctq__sd__sleep_inertia
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__bed__end__24h_t(
data,
name = "ph_y_mctq__sd__bed__end__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__bed__end__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__bed__end__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - In bed end): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__bed__end__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed end):
Time [36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep_inertia
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__bed__end__36h_t(
data,
name = "ph_y_mctq__sd__bed__end__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__bed__end__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__bed__end__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - In bed start): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__bed__start__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed start):
Time [24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_001__02
-
ph_y_mctq__sd_001__01a
-
ph_y_mctq__sd_001__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__bed__start__24h_t(
data,
name = "ph_y_mctq__sd__bed__start__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__bed__start__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_001__02",
"ph_y_mctq__sd_001__01a",
"ph_y_mctq__sd_001__01b",
"ph_y_mctq__sd__bed__start__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - In bed start): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__bed__start__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed start):
Time [36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_001__02
-
ph_y_mctq__sd_001__01a
-
ph_y_mctq__sd_001__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__bed__start__36h_t(
data,
name = "ph_y_mctq__sd__bed__start__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__bed__start__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_001__02",
"ph_y_mctq__sd_001__01a",
"ph_y_mctq__sd_001__01b",
"ph_y_mctq__sd__bed__start__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - In bed): Sum"
Description
Computes the summary score ph_y_mctq__sd__bed_sum
Munich Chronotype Questionnaire [Youth] (School Day - In bed): Sum
-
Summarized variables:
-
ph_y_mctq__sd__bed__end__36h_t
(intermediate score) -
ph_y_mctq__sd__bed__start__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__bed_sum(
data,
name = "ph_y_mctq__sd__bed_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__bed_sum(data) |>
select(
any_of(c(
"ph_y_mctq__sd__bed_sum"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__end__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_005__02
-
ph_y_mctq__sd_005__01a
-
ph_y_mctq__sd_005__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__end__24h_t(
data,
name = "ph_y_mctq__sd__sleep__end__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep__end__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_005__02",
"ph_y_mctq__sd_005__01a",
"ph_y_mctq__sd_005__01b",
"ph_y_mctq__sd__sleep__end__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__end__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_005__02
-
ph_y_mctq__sd_005__01a
-
ph_y_mctq__sd_005__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__end__36h_t(
data,
name = "ph_y_mctq__sd__sleep__end__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep__end__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_005__02",
"ph_y_mctq__sd_005__01a",
"ph_y_mctq__sd_005__01b",
"ph_y_mctq__sd__sleep__end__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__mid__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time
[24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__onset__24h_t
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__mid__24h_t(
data,
name = "ph_y_mctq__sd__sleep__mid__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep__mid__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep__mid__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__mid__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time
[36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep_period
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__mid__36h_t(
data,
name = "ph_y_mctq__sd__sleep__mid__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep__mid__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep__mid__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__onset__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset):
Time [24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__start__24h_t
(intermediate score) -
ph_y_mctq__sd__sleep_latent
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__onset__24h_t(
data,
name = "ph_y_mctq__sd__sleep__onset__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep__onset__24h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep__onset__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__onset__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset):
Time [36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd__sleep__start__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep_latent
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__onset__36h_t(
data,
name = "ph_y_mctq__sd__sleep__onset__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep__onset__36h_t(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep__onset__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep start): Time [24 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__start__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep start):
Time [24 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_002__02
-
ph_y_mctq__sd_002__01a
-
ph_y_mctq__sd_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__start__24h_t(
data,
name = "ph_y_mctq__sd__sleep__start__24h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep__start__24h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_002__02",
"ph_y_mctq__sd_002__01a",
"ph_y_mctq__sd_002__01b",
"ph_y_mctq__sd__sleep__start__24h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep start): Time [36 hour adjusted]"
Description
Computes the summary score ph_y_mctq__sd__sleep__start__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep start):
Time [36 hour adjusted]
-
Summarized variables:
-
ph_y_mctq__sd_002__02
-
ph_y_mctq__sd_002__01a
-
ph_y_mctq__sd_002__01b
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__start__36h_t(
data,
name = "ph_y_mctq__sd__sleep__start__36h_t",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep__start__36h_t(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_002__02",
"ph_y_mctq__sd_002__01a",
"ph_y_mctq__sd_002__01b",
"ph_y_mctq__sd__sleep__start__36h_t"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep wakenings after sleep onset): Sum"
Description
Computes the summary score ph_y_mctq__sd__sleep__waso_sum
Munich Chronotype Questionnaire [Youth] (School Day - Sleep wakenings
after sleep onset): Sum
-
Summarized variables:
-
ph_y_mctq__sd_004
-
ph_y_mctq__sd_004__01
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep__waso_sum(
data,
name = "ph_y_mctq__sd__sleep__waso_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep__waso_sum(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_004",
"ph_y_mctq__sd_004__01",
"ph_y_mctq__sd__sleep__waso_sum"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Duration"
Description
Computes the summary score ph_y_mctq__sd__sleep_dur
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Duration
-
Summarized variables:
-
ph_y_mctq__sd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__waso_sum
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep_dur(
data,
name = "ph_y_mctq__sd__sleep_dur",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep_dur(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep_dur"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Inertia"
Description
Computes the summary score ph_y_mctq__sd__sleep_inertia
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Inertia
-
Summarized variables:
-
ph_y_mctq__sd_006
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep_inertia(
data,
name = "ph_y_mctq__sd__sleep_inertia",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep_inertia(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_006",
"ph_y_mctq__sd__sleep_inertia"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Latency"
Description
Computes the summary score ph_y_mctq__sd__sleep_latent
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Latency
-
Summarized variables:
-
ph_y_mctq__sd_003
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep_latent(
data,
name = "ph_y_mctq__sd__sleep_latent",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd__sleep_latent(data)
select(
data,
any_of(c(
"ph_y_mctq__sd_003",
"ph_y_mctq__sd__sleep_latent"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Period"
Description
Computes the summary score ph_y_mctq__sd__sleep_period
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Period
-
Summarized variables:
-
ph_y_mctq__sd__sleep__end__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__onset__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd__sleep_period(
data,
name = "ph_y_mctq__sd__sleep_period",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sd__sleep_period(data) |>
select(
any_of(c(
"ph_y_mctq__sd__sleep_period"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (School Day): Count"
Description
Computes the summary score ph_y_mctq__sd_count
Munich Chronotype Questionnaire [Youth] (School Day): Count
-
Summarized variables:
-
ph_y_mctq__school_001
-
ph_y_mctq__school_001__01
-
ph_y_mctq__school_001__v01
-
ph_y_mctq__school_001__01__v1
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sd_count(data, name = "ph_y_mctq__sd_count", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_ph_y_mctq__sd_count(data)
select(
data,
any_of(c(
"ph_y_mctq__school_001",
"ph_y_mctq__school_001__01",
"ph_y_mctq__school_001__v01",
"ph_y_mctq__school_001__01__v1",
"ph_y_mctq__sd_count"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Sleep): Duration"
Description
Computes the summary score ph_y_mctq__sleep_dur
Munich Chronotype Questionnaire [Youth] (Sleep): Duration
-
Summarized variables:
-
ph_y_mctq__sd_count
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score) -
ph_y_mctq__fd__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sleep_dur(
data,
name = "ph_y_mctq__sleep_dur",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sleep_dur(data) |>
select(
any_of(c(
"ph_y_mctq__sleep_dur"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Sleep): Loss"
Description
Computes the summary score ph_y_mctq__sleep_loss
Munich Chronotype Questionnaire [Youth] (Sleep): Loss
-
Summarized variables:
-
ph_y_mctq__fd__sleep_dur
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score) -
ph_y_mctq__sd_count
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sleep_loss(
data,
name = "ph_y_mctq__sleep_loss",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sleep_loss(data) |>
select(
any_of(c(
"ph_y_mctq__sleep_loss"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Sleep): Period"
Description
Computes the summary score ph_y_mctq__sleep_period
Munich Chronotype Questionnaire [Youth] (Sleep): Period
-
Summarized variables:
-
ph_y_mctq__sd_count
(intermediate score) -
ph_y_mctq__sd__sleep_period
(intermediate score) -
ph_y_mctq__fd__sleep_period
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__sleep_period(
data,
name = "ph_y_mctq__sleep_period",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__sleep_period(data) |>
select(
any_of(c(
"ph_y_mctq__sleep_period"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Social Jetlag: Absolute): Time"
Description
Computes the summary score ph_y_mctq__socjl_absl
Munich Chronotype Questionnaire [Youth] (Social Jetlag: Absolute):
Time
-
Summarized variables:
-
ph_y_mctq__fd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__mid__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__socjl_absl(
data,
name = "ph_y_mctq__socjl_absl",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__socjl_absl(data) |>
select(
any_of(c(
"ph_y_mctq__socjl_absl"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Social Jetlag: Relative): Time"
Description
Computes the summary score ph_y_mctq__socjl_rel
Munich Chronotype Questionnaire [Youth] (Social Jetlag: Relative):
Time
-
Summarized variables:
-
ph_y_mctq__fd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__mid__36h_t
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq__socjl_rel(
data,
name = "ph_y_mctq__socjl_rel",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq__socjl_rel(data) |>
select(
any_of(c(
"ph_y_mctq__socjl_rel"
))
)
## End(Not run)
Compute all the MCTQ variables
Description
Compute all the MCTQ variables
Usage
compute_ph_y_mctq_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Details
Make sure the data
is the full set of all variables from MCTQ.
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_y_mctq_all(data)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth] (Chronotype): Time"
Description
Computes the summary score ph_y_mctq_chrono
Munich Chronotype Questionnaire [Youth] (Chronotype): Time
-
Summarized variables:
-
ph_y_mctq__fd_007
-
ph_y_mctq__fd__sleep_dur
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score) -
ph_y_mctq__fd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq_chrono(data, name = "ph_y_mctq_chrono", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq_chrono(data) |>
select(
any_of(c(
"ph_y_mctq_chrono"
))
)
## End(Not run)
Compute "Munich Chronotype Questionnaire [Youth]: Outlier"
Description
Computes the summary score ph_y_mctq_outlier
Munich Chronotype Questionnaire [Youth]: Outlier
-
Summarized variables:
-
ph_y_mctq__sd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__onset__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__fd__sleep__mid__36h_t
(intermediate score) -
ph_y_mctq__sd__sleep_dur
(intermediate score) -
ph_y_mctq__fd__sleep_dur
(intermediate score)
-
-
Excluded values: none
Usage
compute_ph_y_mctq_outlier(data, name = "ph_y_mctq_outlier", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_mctq_outlier(data) |>
select(
any_of(c(
"ph_y_mctq_outlier"
))
)
## End(Not run)
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Female): Approximate tanner stages - Number missing"
Description
Computes the summary score ph_y_pds__f__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Approximate tanner stages - Number missing
-
Summarized variables:
-
ph_y_pds_002
-
ph_y_pds__f_001
-
ph_y_pds__f_002
-
-
Excluded values:
777
999
Usage
compute_ph_y_pds__f__categ_nm(
data,
name = "ph_y_pds__f__categ_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Female): Number missing"
Description
Computes the summary score ph_y_pds__f_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Number missing
-
Summarized variables:
-
ph_y_pds_001
-
ph_y_pds_002
-
ph_y_pds_003
-
ph_y_pds__f_001
-
ph_y_pds__f_002
-
-
Excluded values:
777
999
Usage
compute_ph_y_pds__f_nm(
data,
name = "ph_y_pds__f_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Male): Approximate tanner stages - Number missing"
Description
Computes the summary score ph_y_pds__m__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Approximate tanner stages - Number missing
-
Summarized variables:
-
ph_y_pds_002
-
ph_y_pds__m_001
-
ph_y_pds__m_002
-
-
Excluded values:
777
999
Usage
compute_ph_y_pds__m__categ_nm(
data,
name = "ph_y_pds__m__categ_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Male): Number missing"
Description
Computes the summary score ph_y_pds__m_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Number missing
-
Summarized variables:
-
ph_y_pds_001
-
ph_y_pds_002
-
ph_y_pds_003
-
ph_y_pds__m_001
-
ph_y_pds__m_002
-
-
Excluded values:
777
999
Usage
compute_ph_y_pds__m_nm(
data,
name = "ph_y_pds__m_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the ph_y_pds
summary scores
Description
This is a high-level function that computes all summary scores in this table.
Make sure the data
contains all the necessary columns.
Usage
compute_ph_y_pds_all(data)
Arguments
data |
tbl. Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_ph_y_pds_all(data)
## End(Not run)
Compute "Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative expectancies): Number missing"
Description
Computes the summary score su_y_alcexp__neg_nm
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative
expectancies): Number missing
-
Summarized variables:
-
su_y_alcexp__neg_001
-
su_y_alcexp__neg_002
-
su_y_alcexp__neg_003
-
-
Excluded values: none
Usage
compute_su_y_alcexp__neg_nm(data, name = "su_y_alcexp__neg_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_alcexp__neg_prsum()
Compute "Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive expectancies): Number missing"
Description
Computes the summary score su_y_alcexp__pos_nm
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive
expectancies): Number missing
-
Summarized variables:
-
su_y_alcexp__pos_001
-
su_y_alcexp__pos_002
-
su_y_alcexp__pos_003
-
-
Excluded values: none
Usage
compute_su_y_alcexp__pos_nm(data, name = "su_y_alcexp__pos_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_alcexp__pos_prsum()
Compute all the su_y_alcexp scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_alcexp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_alcexp_all(data)
## End(Not run)
Compute all Alcohol Hangover Symptoms Scale (HSS) Youth summary scores
Description
compute all summary scores of Alcohol Hangover Symptoms Scale (HSS) Youth
Usage
compute_su_y_alchss_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_su_y_alchss_all(data)
## End(Not run)
Compute "Alcohol Hangover Symptoms Scale (HSS) [Youth]: Count"
Description
Computes the summary score su_y_alchss_count
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Count
-
Summarized variables:
-
su_y_alchss_001
-
su_y_alchss_002
-
su_y_alchss_003
-
su_y_alchss_004
-
su_y_alchss_005
-
su_y_alchss_006
-
su_y_alchss_007
-
su_y_alchss_008
-
su_y_alchss_009
-
su_y_alchss_010
-
su_y_alchss_011
-
su_y_alchss_012
-
su_y_alchss_013
-
su_y_alchss_014
-
su_y_alchss_001__l
-
su_y_alchss_002__l
-
su_y_alchss_003__l
-
su_y_alchss_004__l
-
su_y_alchss_005__l
-
su_y_alchss_006__l
-
su_y_alchss_007__l
-
su_y_alchss_008__l
-
su_y_alchss_009__l
-
su_y_alchss_010__l
-
su_y_alchss_011__l
-
su_y_alchss_012__l
-
su_y_alchss_013__l
-
su_y_alchss_014__l
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
compute_su_y_alchss_count(
data,
name = "su_y_alchss_count",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_su_y_alchss_count(data) |> View()
## End(Not run)
Compute "Alcohol Hangover Symptoms Scale (HSS) [Youth]: Number missing"
Description
Computes the summary score su_y_alchss_nm
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Number missing
-
Summarized variables:
-
su_y_alchss_001
-
su_y_alchss_002
-
su_y_alchss_003
-
su_y_alchss_004
-
su_y_alchss_005
-
su_y_alchss_006
-
su_y_alchss_007
-
su_y_alchss_008
-
su_y_alchss_009
-
su_y_alchss_010
-
su_y_alchss_011
-
su_y_alchss_012
-
su_y_alchss_013
-
su_y_alchss_014
-
su_y_alchss_001__l
-
su_y_alchss_002__l
-
su_y_alchss_003__l
-
su_y_alchss_004__l
-
su_y_alchss_005__l
-
su_y_alchss_006__l
-
su_y_alchss_007__l
-
su_y_alchss_008__l
-
su_y_alchss_009__l
-
su_y_alchss_010__l
-
su_y_alchss_011__l
-
su_y_alchss_012__l
-
su_y_alchss_013__l
-
su_y_alchss_014__l
-
-
Excluded values: none
Usage
compute_su_y_alchss_nm(data, name = "su_y_alchss_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Examples
## Not run:
compute_su_y_alchss_nm(data)
## End(Not run)
Compute all the su_y_alcprob scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_alcprob_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_alcprob_all(data)
## End(Not run)
Compute "Alcohol Problem Index (RAPI) [Youth]: Number missing"
Description
Computes the summary score su_y_alcprob_nm
Alcohol Problem Index (RAPI) [Youth]: Number missing
-
Summarized variables:
-
ab_p_demo__race_001___0
-
ab_p_demo__race_001___10
-
ab_p_demo__race_001___11
-
ab_p_demo__race_001___12
-
ab_p_demo__race_001___13
-
ab_p_demo__race_001___14
-
ab_p_demo__race_001___15
-
ab_p_demo__race_001___16
-
ab_p_demo__race_001___17
-
ab_p_demo__race_001___18
-
ab_p_demo__race_001___19
-
ab_p_demo__race_001___20
-
ab_p_demo__race_001___21
-
ab_p_demo__race_001___22
-
ab_p_demo__race_001___23
-
ab_p_demo__race_001___24
-
ab_p_demo__race_001___25
-
ab_p_demo__race_001___777
-
ab_p_demo__race_001___999
-
ab_p_demo__race_001__v01___999
-
ab_p_demo__race_001__v01___10
-
ab_p_demo__race_001__v01___11
-
ab_p_demo__race_001__v01___12
-
ab_p_demo__race_001__v01___20
-
ab_p_demo__race_001__v01___21
-
ab_p_demo__race_001__v01___22
-
ab_p_demo__race_001__v01___23
-
ab_p_demo__race_001__v01___13
-
ab_p_demo__race_001__v01___14
-
ab_p_demo__race_001__v01___15
-
ab_p_demo__race_001__v01___17
-
ab_p_demo__race_001__v01___18
-
ab_p_demo__race_001__v01___19
-
ab_p_demo__race_001__v01___16
-
ab_p_demo__race_001__v01___24
-
ab_p_demo__race_001__v01___777
-
-
Excluded values: none
Usage
compute_su_y_alcprob_nm(data, name = "su_y_alcprob_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Alcohol Subject Response and Effects [Youth] (Last 6 months): Count [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__6mo_count
Alcohol Subject Response and Effects [Youth] (Last 6 months): Count
[Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__6mo_001
-
su_y_alcsre__6mo_002
-
su_y_alcsre__6mo_003
-
su_y_alcsre__6mo_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_su_y_alcsre__6mo_count(
data,
name = "su_y_alcsre__6mo_count",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (Last 6 months): Number missing"
Description
Computes the summary score su_y_alcsre__6mo_nm
Alcohol Subject Response and Effects [Youth] (Last 6 months): Number
missing
-
Summarized variables:
-
su_y_alcsre__6mo_001
-
su_y_alcsre__6mo_002
-
su_y_alcsre__6mo_003
-
su_y_alcsre__6mo_004
-
-
Excluded values: none
Usage
compute_su_y_alcsre__6mo_nm(data, name = "su_y_alcsre__6mo_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (First 5 times ever drank): Count [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__first5_count
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Count [Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__first5_001
-
su_y_alcsre__first5_002
-
su_y_alcsre__first5_003
-
su_y_alcsre__first5_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_su_y_alcsre__first5_count(
data,
name = "su_y_alcsre__first5_count",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (First 5 times ever drank): Number missing"
Description
Computes the summary score su_y_alcsre__first5_nm
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Number missing
-
Summarized variables:
-
su_y_alcsre__first5_001
-
su_y_alcsre__first5_002
-
su_y_alcsre__first5_003
-
su_y_alcsre__first5_004
-
-
Excluded values: none
Usage
compute_su_y_alcsre__first5_nm(
data,
name = "su_y_alcsre__first5_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (Heaviest drinking period): Count [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__hvy_count
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Count [Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__hvy_001
-
su_y_alcsre__hvy_002
-
su_y_alcsre__hvy_003
-
su_y_alcsre__hvy_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
compute_su_y_alcsre__hvy_count(
data,
name = "su_y_alcsre__hvy_count",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (Heaviest drinking period): Number missing"
Description
Computes the summary score su_y_alcsre__hvy_nm
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Number missing
-
Summarized variables:
-
su_y_alcsre__hvy_001
-
su_y_alcsre__hvy_002
-
su_y_alcsre__hvy_003
-
su_y_alcsre__hvy_004
-
-
Excluded values: none
Usage
compute_su_y_alcsre__hvy_nm(data, name = "su_y_alcsre__hvy_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for su_y_alcsre.
Description
This function computes all summary scores for the su_y_alcsre form. Make sure to have all necessary columns in the data frame.
Usage
compute_su_y_alcsre_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_alcsre_all(data)
## End(Not run)
Compute all the SU youth caff scores
Description
A single function to compute all caff scores in SU domain.
Usage
compute_su_y_caff_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of negative expectancies): Number missing"
Description
Computes the summary score su_y_cigexp__neg_nm
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Number missing
-
Summarized variables:
-
su_y_cigexp__neg_001
-
su_y_cigexp__neg_002
-
-
Excluded values: none
Usage
compute_su_y_cigexp__neg_nm(data, name = "su_y_cigexp__neg_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_cigexp__neg_prsum()
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of negative expectancies): Prorated sum (v01)"
Description
Computes the summary score su_y_cigexp__neg_prsum__v01
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Prorated sum (v01)
Note: all 0s are changed to 1s prior to calculating pro-rated sum
-
Summarized variables:
-
su_y_cigexp__neg_001
-
su_y_cigexp__neg_002
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
compute_su_y_cigexp__neg_prsum__v01(
data,
name = "su_y_cigexp__neg_prsum__v01",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_cigexp__neg_prsum()
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of positive expectancies): Number missing"
Description
Computes the summary score su_y_cigexp__pos_nm
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Number missing
-
Summarized variables:
-
su_y_cigexp__pos_001
-
su_y_cigexp__pos_002
-
su_y_cigexp__pos_003
-
su_y_cigexp__pos_004
-
-
Excluded values: none
Usage
compute_su_y_cigexp__pos_nm(data, name = "su_y_cigexp__pos_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_cigexp__pos_prsum()
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of positive expectancies): Prorated sum (v01)"
Description
Computes the summary score su_y_cigexp__pos_prsum__v01
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Prorated sum (v01) [Validation: No more than 2
missing or declined]
Note: all 0s are changed to 1s prior to calculating pro-rated sum
-
Summarized variables:
-
su_y_cigexp__pos_001
-
su_y_cigexp__pos_002
-
su_y_cigexp__pos_003
-
su_y_cigexp__pos_004
-
-
Excluded values: none
-
Validation criterion: maximally 2 of 4 items missing
-
Notes:
Values in all input variables were recoded:
"0" –> "1"
Usage
compute_su_y_cigexp__pos_prsum__v01(
data,
name = "su_y_cigexp__pos_prsum__v01",
combine = TRUE,
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_cigexp__pos_prsum()
Compute all the su_y_cigexp scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_cigexp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_cigexp_all(data)
## End(Not run)
Compute all the su_y_drgprob scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_drgprob_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_drgprob_all(data)
## End(Not run)
Compute "Drug Problem Index (DAPI) [Youth]: Number missing"
Description
Computes the summary score su_y_drgprob_nm
Drug Problem Index (DAPI) [Youth]: Number missing
-
Summarized variables:
-
su_y_drgprob_001
-
su_y_drgprob_002
-
su_y_drgprob_003
-
su_y_drgprob_004
-
su_y_drgprob_005
-
su_y_drgprob_006
-
su_y_drgprob_007
-
su_y_drgprob_008
-
su_y_drgprob_009
-
su_y_drgprob_010
-
su_y_drgprob_012
-
su_y_drgprob_013
-
su_y_drgprob_014
-
su_y_drgprob_015
-
su_y_drgprob_016
-
su_y_drgprob_017
-
su_y_drgprob_018
-
-
Excluded values: none
Usage
compute_su_y_drgprob_nm(data, name = "su_y_drgprob_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute all the SU youth exp scores
Description
A single function to compute all EXP scores in SU domain.
Usage
compute_su_y_exp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Compute "Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative expectancies): Number missing"
Description
Computes the summary score su_y_mjexp__neg_nm
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative
expectancies): Number missing
-
Summarized variables:
-
su_y_mjexp__neg_001
-
su_y_mjexp__neg_002
-
su_y_mjexp__neg_003
-
-
Excluded values: none
Usage
compute_su_y_mjexp__neg_nm(data, name = "su_y_mjexp__neg_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_mjexp__neg_prsum()
Compute "Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive expectancies): Number missing"
Description
Computes the summary score su_y_mjexp__pos_nm
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive
expectancies): Number missing
-
Summarized variables:
-
su_y_mjexp__pos_001
-
su_y_mjexp__pos_002
-
su_y_mjexp__pos_003
-
-
Excluded values: none
Usage
compute_su_y_mjexp__pos_nm(data, name = "su_y_mjexp__pos_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_mjexp__pos_prsum()
Compute all the su_y_mjexp scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_mjexp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_mjexp_all(data)
## End(Not run)
Compute all the su_y_mjprob scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_mjprob_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_mjprob_all(data)
## End(Not run)
Compute "Marijuana Problem Index (MAPI) [Youth]: Number missing"
Description
Computes the summary score su_y_mjprob_nm
Marijuana Problem Index (MAPI) [Youth]: Number missing
-
Summarized variables:
-
su_y_mjprob_001
-
su_y_mjprob_002
-
su_y_mjprob_003
-
su_y_mjprob_004
-
su_y_mjprob_005
-
su_y_mjprob_006
-
su_y_mjprob_007
-
su_y_mjprob_008
-
su_y_mjprob_009
-
su_y_mjprob_010
-
su_y_mjprob_011
-
su_y_mjprob_012
-
su_y_mjprob_016
-
su_y_mjprob_017
-
su_y_mjprob_018
-
-
Excluded values: none
Usage
compute_su_y_mjprob_nm(data, name = "su_y_mjprob_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
Compute "Marijuana Subjective Response and Effects [Youth] (Negative): Number missing"
Description
Computes the summary score su_y_mjsre__neg_nm
Marijuana Subjective Response and Effects [Youth] (Negative): Number
missing
-
Summarized variables:
-
su_y_mjsre__neg_001
-
su_y_mjsre__neg_002
-
su_y_mjsre__neg_003
-
su_y_mjsre__neg_004
-
su_y_mjsre__neg_005
-
su_y_mjsre__neg_006
-
su_y_mjsre__neg_007
-
su_y_mjsre__neg_008
-
-
Excluded values: none
Usage
compute_su_y_mjsre__neg_nm(data, name = "su_y_mjsre__neg_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Subjective Response and Effects [Youth] (Positive): Number missing"
Description
Computes the summary score su_y_mjsre__pos_nm
Marijuana Subjective Response and Effects [Youth] (Positive): Number
missing
-
Summarized variables:
-
su_y_mjsre__pos_001
-
su_y_mjsre__pos_002
-
su_y_mjsre__pos_003
-
-
Excluded values: none
Usage
compute_su_y_mjsre__pos_nm(data, name = "su_y_mjsre__pos_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for su_y_mjsre.
Description
This function computes all summary scores for the su_y_mjsre form. Make sure to have all necessary columns in the data frame.
Usage
compute_su_y_mjsre_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_mjsre_all(data)
## End(Not run)
Compute "Marijuana Subjective Response and Effects [Youth] (NA): Number missing"
Description
Computes the summary score su_y_mjsre_nm
Marijuana Subjective Response and Effects [Youth] (NA): Number missing
-
Summarized variables:
-
su_y_mjsre__pos_001
-
su_y_mjsre__pos_002
-
su_y_mjsre__pos_003
-
su_y_mjsre__neg_001
-
su_y_mjsre__neg_002
-
su_y_mjsre__neg_003
-
su_y_mjsre__neg_004
-
su_y_mjsre__neg_005
-
su_y_mjsre__neg_006
-
su_y_mjsre__neg_007
-
su_y_mjsre__neg_008
-
-
Excluded values: none
Usage
compute_su_y_mjsre_nm(data, name = "su_y_mjsre_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Positive and negative effects of first smokeless tobacco or chew use): Number missing"
Description
Computes the summary score su_y_nicsre__chew_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first smokeless tobacco or chew use): Number missing
-
Summarized variables:
-
su_y_nicsre__chew__pos_001
-
su_y_nicsre__chew__neg_001
-
-
Excluded values: none
Usage
compute_su_y_nicsre__chew_nm(
data,
name = "su_y_nicsre__chew_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Positive and negative effects of first cigarette use): Number missing"
Description
Computes the summary score su_y_nicsre__cig_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first cigarette use): Number missing
-
Summarized variables:
-
su_y_nicsre__cig__pos_001
-
su_y_nicsre__cig__neg_001
-
-
Excluded values: none
Usage
compute_su_y_nicsre__cig_nm(data, name = "su_y_nicsre__cig_nm", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Positive and negative effects of first vape use): Number missing"
Description
Computes the summary score su_y_nicsre__vape_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first vape use): Number missing
-
Summarized variables:
-
su_y_nicsre__vape__pos_001
-
su_y_nicsre__vape__pos_001__v01
-
su_y_nicsre__vape__neg_001
-
su_y_nicsre__vape__neg_001__v01
-
-
Excluded values: none
Usage
compute_su_y_nicsre__vape_nm(
data,
name = "su_y_nicsre__vape_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute all summary scores for su_y_nicsre.
Description
This function computes all summary scores for the su_y_nicsre form. Make sure to have all necessary columns in the data frame.
Usage
compute_su_y_nicsre_all(data)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_nicsre_all(data)
## End(Not run)
Compute "ENDS Expectancies [Youth] (Strength of negative expectancies): Number missing"
Description
Computes the summary score su_y_nicvapeexp__neg_nm
ENDS Expectancies [Youth] (Strength of negative expectancies): Number
missing
-
Summarized variables:
-
su_y_nicvapeexp__neg_001
-
su_y_nicvapeexp__neg_002
-
su_y_nicvapeexp__neg_003
-
su_y_nicvapeexp__neg_004
-
-
Excluded values: none
Usage
compute_su_y_nicvapeexp__neg_nm(
data,
name = "su_y_nicvapeexp__neg_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_nicvapeexp__neg_prsum()
Compute "ENDS Expectancies [Youth] (Strength of positive expectancies): Number missing"
Description
Computes the summary score su_y_nicvapeexp__pos_nm
ENDS Expectancies [Youth] (Strength of positive expectancies): Number
missing
-
Summarized variables:
-
su_y_nicvapeexp__pos_001
-
su_y_nicvapeexp__pos_002
-
su_y_nicvapeexp__pos_003
-
su_y_nicvapeexp__pos_004
-
-
Excluded values: none
Usage
compute_su_y_nicvapeexp__pos_nm(
data,
name = "su_y_nicvapeexp__pos_nm",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_su_y_nicvapeexp__pos_prsum()
Compute all the su_y_nicvapeexp scores
Description
A single function to compute all scores in the above domain using default arguments.
Usage
compute_su_y_nicvapeexp_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Examples
## Not run:
compute_su_y_nicvapeexp_all(data)
## End(Not run)
Compute all the SU youth prob scores
Description
A single function to compute all PROB scores in SU domain.
Usage
compute_su_y_prob_all(data)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
Value
tbl. The input data frame with the summary scores appended as new columns.
Count days since last use of a given substance
Description
Computes the number of days since the last use of a given substance
as of the day of the substance use interview.
Returns NA
for the participants with no reported use of the provided
substance.
Usage
compute_su_y_sui__last__day_count(data, name, substance, combine = TRUE)
Arguments
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_su_y_sui__last__day_count(
data = data_sui,
name = "su_y_sui__alc__last__day_count",
substance = "alc"
)
## End(Not run)
Compute age of regular use for a given substance
Description
Computes the age (in years) of regular use of a given substance.
Returns NA
for the participants with no regular use of the provided
substance reported.
Usage
compute_su_y_sui__reg_useage(data, name, substance, combine = TRUE)
Arguments
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_su_y_sui__reg_useage(
data = data_sui,
name = "su_y_sui__alc__reg_useage",
substance = "alc"
)
## End(Not run)
Compute TLFB first or last date of substance use
Description
Computes either the first or last date of use for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering days with co-use of (a)other substance(s); and/or only binge use.
Usage
compute_tlfb_dt(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
co_use = NULL,
binge = NULL,
position
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
position |
character. The position of the substance use event. Must be
one of |
Value
A tibble with the computed score for each participant/event.
See Also
Examples
## Not run:
compute_tlfb_dt(
data = data_tlfb,
name = "su_y_tlfb__alc__first__cum_dt",
substance = "Alcohol",
position = "first"
)
## End(Not run)
Compute TLFB maximum dose
Description
Computes the maximum dose over all use days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
Usage
compute_tlfb_maxdose(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Value
A tibble with the computed score for each participant/event.
Examples
## Not run:
compute_tlfb_maxdose(
data = data_tlfb,
name = "su_y_tlfb__alc__3mo_maxdose",
substance = "Alcohol",
days = 90
)
## End(Not run)
Compute TLFB mean quantity
Description
Computes the mean quantity per use day for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
Usage
compute_tlfb_mean(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Value
A tibble with the computed score for each participant/event.
Examples
## Not run:
compute_tlfb_mean(
data = data_tlfb,
name = "su_y_tlfb__alc__1mo_mean",
substance = "Alcohol",
days = 30
)
## End(Not run)
Compute TLFB total dose
Description
Computes the total dose over all use day for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
Usage
compute_tlfb_totdose(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Value
A tibble with the computed score for each participant/event.
Examples
## Not run:
compute_tlfb_totdose(
data = data_tlfb,
name = "su_y_tlfb__alc__binge_totdose",
substance = "Alcohol",
binge = list("F" = 4, "M" = 5)
)
## End(Not run)
Compute TLFB use days
Description
Computes the number of use days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
Usage
compute_tlfb_ud(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Value
A tibble with the computed score for each participant/event.
Examples
## Not run:
compute_tlfb_ud(
data = data_tlfb,
name = "su_y_tlfb__alc__1mo__wknd_ud",
substance = "Alcohol",
days = 30,
wknd = TRUE
)
## End(Not run)
Convert MCTQ time data to 24h or 36 format
Description
Utility function to convert MCTQ survey responses to 24h or 36h format times.
Usage
convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, scale = "24h")
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the new column with the summary score. |
col_hrs_a |
character. The name of the column with the first time. 1, 4 AM | 2, 5 AM | 3, 6 AM | 4, 7 AM | 5, 8 AM | 6, 9 AM | 7, 10 AM | 8, 11 AM | 9, 12 PM | 10, 1 PM | 11, 2 PM | 12, 3 PM | 13, 4 PM |
col_hrs_b |
character. The name of the column with the second time. 1, 5 PM | 2, 6 PM | 3, 7 PM | 4, 8 PM | 5, 9 PM | 6, 10 PM | 7, 11 PM | 8, 12 AM | 9, 1 AM | 10, 2 AM | 11, 3 AM |
col_minute |
character. The name of the column with the minutes. If the
column value is 1, 0 minutes | 2, 5 minutes | 3, 10 minutes | 4, 15 minutes | 5, 20 minutes | 6, 25 minutes | 7, 30 minutes | 8, 35 minutes | 9, 40 minutes | 10, 45 minutes | 11, 50 minutes | 12, 55 minutes |
scale |
character. The scale of the time format. Default is "24h". The other option is "36h". |
Details
Expect values 0 <= value < 24 for 24h format. Expect values 12 <= value < 36 for 36h format.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
col_hrs_a <- "ph_y_mctq__fd_001__01a"
col_hrs_b <- "ph_y_mctq__fd_001__01b"
col_minute <- "ph_y_mctq__fd_001__02"
name <- "ph_y_mctq__fd__bed__start__24h_t"
data <- dplyr::tibble(
ph_y_mctq__fd_001__01a = c(NA, NA, NA, NA, NA, 1, 7, 3, NA),
ph_y_mctq__fd_001__01b = c(6, 7, 8, 8, 10, NA, NA, NA, NA),
ph_y_mctq__fd_001__02 = c(1, 1, 1, 7, 7, 1, 4, 1, NA)
)
convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute)
name <- "ph_y_mctq__fd__bed__start__36h_t"
convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, "36h")
Sample dataset of Timeline Followback assessment
Description
Sample TLFB data for testing and examples.
Usage
data_tlfb_sample
Format
An object of class tbl_df
(inherits from tbl
, data.frame
) with 8 rows and 10 columns.
Dummy function for all ASEBA summary score functions.
Description
Dummy function for all ASEBA summary score functions.
Usage
dummy_aseba(data, data_norm, name, max_na, col_age, col_sex, exclude, combine)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Value
tbl. see combine
.
Dummy function for all MH summary score functions.
Description
Dummy function for all MH summary score functions.
Usage
dummy_mh(data, name, max_na, combine, exclude, event, events)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
combine |
logical. If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
event |
character. Event (session ID) to be used. |
events |
character vector. Event (session ID) to be used. |
Value
tbl. see combine
.
Dummy function for all OBTI score functions.
Description
Dummy function for all OBTI score functions.
Usage
dummy_ph_p_otbi(data, name, combine, max_na, exclude)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
Value
tbl. see combine
.
Filter TLFB data
Description
This function filters the TLFB (Timeline Followback) data based on specified substance(s); period (estimated vs. detailed); number of days before the TLFB interview; weekend-only usage; co-use of other substances; and/or binge use.
Usage
filter_tlfb(
data,
substance = NULL,
period = NULL,
days = NULL,
wknd = NULL,
co_use = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Value
A filtered data frame based on the specified criteria.
Examples
## Not run:
filtered_data <- filter_tlfb(
data,
substance = "Alcohol",
wknd_only = TRUE,
period = "estimated",
days = 30
)
## End(Not run)
Get T-score table from list of tscores (Internal)
Description
This function retrieves the tscore table from a list of tscores based on the function name. The function should be used internally.
Usage
get_tscore_tbl(list_tscore, func_name)
Arguments
list_tscore |
list. List of tscores. see details. |
func_name |
character. The name of the function. |
Details
The list_tscore
should be a list of prepared tscore tables. The list has
two layers of structure: the first layer is the name of form, and the second
layer is the keyword of the tscore table.
list |- form_1 | |- keyword_1 | |- keyword_2 | |- ... |- form_2 | |- keyword_1 | |- keyword_2 | |- ... |- ...
This object is prepared by the DSM team and for internal users, please ask
the DSM team for the rds
file.
Forms and keywords
Forms and keywords are based on the function names. A function should contain
both the form and keyword in its name, with only one exception being the
overall score of a form, which does not have a keyword. The function name
should be in the format of compute_form_xx__keyword_tscore
or
compute_form_xx_tscore
. The function name will be split by _
and
the unique keywords will be used to search for the tscore table.
Value
tbl. The tscore table. If there is no match or more than one match, an error will be thrown.
Examples
## Not run:
list_tscore <- readRDS("aseba_tscore.rds")
get_tscore_tbl(list_tscore, "compute_mh_p_abcl__afs__frnd_tscore")
## End(Not run)
Insert references into help files
Description
Inserts references into help files in markdown format. The function takes the a single score name and returns the reference in markdown format.
Usage
insert_reference(name, tbl_ref_name = "tbl_ref")
Arguments
name |
character, The name of the score to insert the reference for. |
tbl_ref_name |
character, The name of the reference table object in the environment. |
Details
It is expected to have a table with the following columns in environment:
-
name
: The name of the scores -
authors
: The authors of the paper -
year
: The year of publication -
title
: The title of the paper -
journal
: The journal where the paper was published -
volume_page
: The volume and page number of the paper, optional, can be""
if not available -
doi
: The DOI of the paper, optional, can be""
if not available
Value
character (vector). The reference in markdown format.
Examples
tbl_ref <- tibble::tibble(
name = c("score1", "score1", "score2"),
authors = c(
"Smith, B., Jones, A.",
"Simon, J., Norman, D. A.",
"Smith, B., Jones, A., Simon, J., Norman, D. A."
),
year = c(2020, 2021, 2022),
title = c(
"Title of the First Paper",
"Title of the Second Paper",
"Title of the Third Paper"
),
journal = c("Journal A", "Journal B", "Journal C"),
volume_page = c("1(1): 1-10", "", "3(3): 21-30"),
doi = c("https://10.1234/abc", "https://10.1234/def", "")
)
insert_reference("score1")
Create static variable, one per participant, using longitudinal responses
Description
Update an existing field to include longitudinal responses.
Use data for each id
from the first available event
and
set that value for all event
rows.
Usage
make_static(
data,
id = "participant_id",
event = "session_id",
exclude = NULL,
var_in,
var_out
)
Arguments
data |
Dataframe with fields specified in |
id |
character of length 1. Name of field that contains the IDs for which we need to assess the longitudinal data. |
event |
character of length 1. Name of field that contains the (longitudinal) event IDs. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
var_in |
character of length 1. Name of the field that contains the longitudinal values or responses. |
var_out |
character of length 1. Name of the new field that contains
one static value per |
Value
Dataframe with two columns: id
and var_out
Examples
data <- tibble::tribble(
~"id", ~"event", ~"values",
"A", 1, NA,
"A", 2, 2,
"A", 3, 3,
"B", 1, NA,
"B", 2, NA,
"B", 3, 1
)
make_static(
data,
var_in = "values",
var_out = "static_nothing_excluded",
id = "id",
event = "event"
)
make_static(
data,
var_in = "values",
var_out = "static_excluding_1and2",
exclude = c("1", "2"),
id = "id",
event = "event"
)
Markdown bullet point list
Description
Creates a bullet point list in markdown format. Copy of
gluedown::md_bullet()
but with the added ability to specify an indent to
create nested lists and the option to use code font.
Usage
md_bullet(
x,
indent = 0,
code = FALSE,
italic = FALSE,
marker = c("*", "-", "+")
)
Arguments
x |
character (vector). Text to convert into a bullet point list. |
indent |
numeric, positive whole number. Number of spaces to indent the bullet point list by (Default: 0). |
code |
logical. If the text will be formatted as code (Default: TRUE). |
italic |
logical. If the text will be formatted as italic (Default: FALSE). |
marker |
character. The bullet list marker to use (Default: "*"). |
Value
glue
vector. A bullet point list in markdown format.
Examples
md_bullet(c("First item", "Second item", "Third item"), code = TRUE)
md_bullet(c("First item", "Second item", "Third item"), indent = 2)
Retain values based on conditions
Description
Creates new variables by applying conditions to specified columns
(fork_vars
) and retaining or modifying values from other columns (vars
)
based on keep_values
.
Generates new variables with _product
suffix.
Usage
product_vars(data, fork_vars, vars, keep_values)
Arguments
data |
A data frame containing the input data |
fork_vars |
Character vector of column names to use as logical
conditions, evaluated against |
vars |
Character vector of column names whose values will be retained or
modified based on conditions in |
keep_values |
Vector of values in |
Value
A data frame with new _product
suffixed variables. Excludes
intermediate logical columns.
Examples
product_vars(
data = tibble::tibble(
var_av = c("1", "2", "3", "4", "5", NA, "999", "777"),
var_al = c("5", "4", "3", "2", "1", "777", NA, "999"),
var_bv = c("1", "1", "36", "2", "1", NA, "999", "777"),
var_bl = c("5", "2", "2", "2", "1", "777", NA, "999")
),
fork_vars = c("var_al", "var_bl"),
vars = c("var_av", "var_bv"),
keep_values = "2"
)
Recode levels
Description
Recodes specified levels of a character/factor variable, e.g., to apply reverse coding before summary score computation.
Usage
recode_levels(data, vars, recode, temp = FALSE)
Arguments
data |
tbl. Data frame containing the columns to be recoded. |
vars |
character (vector). The name(s) of the column(s) to be recoded. |
recode |
named character vector. The levels to be recoded, with the name being the original value and the value being the value to recode to. |
temp |
logical. If |
Value
tbl. The input data frame with the recoded variable(s).
Examples
data <- tibble::tibble(
var_a = c("1", "2", "3", "4", "5", NA, "999", "777"),
var_b = c("5", "4", "3", "2", "1", "777", NA, "999")
)
# recode individual variables
data |>
recode_levels(
vars = "var_a",
recode = c("999" = "0", "777" = "0")
) |>
recode_levels(
vars = "var_b",
recode = c("999" = "6", "777" = "7")
)
# apply the same recoding to several variables
data |>
recode_levels(
vars = c(
"var_a",
"var_b"
),
recode = c(
"1" = "5",
"2" = "4",
"4" = "2",
"5" = "1"
)
)
Compute the number or count of matching conditions
Description
Computes the number of conditions (provided as a character vectorcond
),
involving the input variables vars
, that were found to be TRUE
.
Options available to exclude certain values from the input variables
(provided as a character vector exclude
).
Usage
ss_count(
data,
name,
vars,
vars_temp = NULL,
exclude = NULL,
combine = FALSE,
allow_missingness = TRUE,
cond
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The name(s) of the column(s) to be summarized. |
vars_temp |
character vector. The name(s) of temporary column(s) used
to compute the summary score. Note, these columns are not checked for
missingness. See |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: FALSE). |
allow_missingness |
logical. Default set to TRUE. If TRUE, summary score
is set to |
cond |
character vector. Each specified condition, involving the values
of specific input fields, gets tested for |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
dat <- tibble::tibble(
id = c("1", "2", "3", "4", "5", "6", "7", "8"),
a_1 = c(1, 1, NA, 1, 1, 1, 1, 1),
a_2 = c(1, NA, NA, 1, 1, NA, 1, 1),
b_1 = c(1, 1, NA, NA, 1, 1, 1, 1),
b_2 = c(1, 1, NA, 1, 1, NA, 1, 1),
c = c(NA, 1, NA, 1, 777, 0, 1, 0)
)
# define conditions to assess
conditions <- c(
"a_1 == 1 & a_2 == 1",
"b_1 == 1 & b_2 == 1",
"c"
)
# count number of matched conditions
ss_count(
data = dat,
name = "ss",
vars = c("a_1", "a_2", "b_1", "b_2", "c"),
cond = conditions,
combine = TRUE
)
ss_count(
data = dat,
name = "ss",
vars = c("a_1", "a_2", "b_1", "b_2", "c"),
cond = conditions,
exclude = c("777"),
combine = TRUE
)
conditions <- paste(
c(
"a_1 == 1 & a_2 == 1",
"b_1 == 1 & b_2 == 1",
"c >= 1"
),
collapse = "&"
)
ss_count(
data = dat,
name = "ss",
vars = c("a_1", "a_2", "b_1", "b_2", "c"),
cond = conditions,
exclude = c("777"),
combine = TRUE
)
ss_count(
data = dat,
name = "ss",
vars = c("a_1", "a_2", "b_1", "b_2", "c"),
cond = conditions,
exclude = c("777"),
allow_missingness = FALSE,
combine = TRUE
)
Compute the number or count of matching conditions
Description
Computes the number of conditions (provided as a character vectorcond
),
involving the input variables vars
, that were found to be TRUE
.
Options available to exclude certain values from the input variables
(provided as a character vector exclude
).
Usage
ss_count_cond(data, name, vars, exclude = NULL, combine = FALSE, cond, max_na)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: FALSE). |
cond |
character vector. Each specified condition, involving the values
of specific input fields, gets tested for |
max_na |
numeric, positive whole number. Number of missing items allowed. |
Value
tbl. The input data frame with the summary score appended as a new column.
Compute max across columns
Description
Computes the max of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
Usage
ss_max(
data,
name,
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tribble(
~id, ~session_id, ~A, ~B, ~C, ~D,
"id1", "1", 1, 5, 2, NA,
"id1", "2", 2, 4, NA, NA,
"id1", "3", 3, 3, 3, 3,
"id1", "4", 4, 2, 4, 2,
"id1", "5", 5, 1, 5, 3
)
ss_max(
data,
name = "summary",
vars = c("A", "B", "C", "D")
)
ss_max(
data,
name = "summary",
vars = c("A", "B", "C", "D"),
max_na = 1,
exclude = c("1")
)
ss_max(
data,
name = "summary",
vars = c("A", "B", "C", "D"),
max_na = 1,
exclude = c("1"),
events = c("4")
)
Compute mean
Description
Computes the mean of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
Usage
ss_mean(
data,
name,
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~d, ~e,
"ses-00A", 1, 1, 1, 1, NA,
"ses-01A", 2, 777, 2, 2, 2,
"ses-02A", 3, 3, 999, 3, 3,
"ses-02A", 4, 4, 4, 777, NA,
"ses-03A", 5, NA, 777, 999, 5,
"ses-03A", NA, NA, NA, NA, NA,
"ses-04A", 1, NA, NA, NA, NA
)
data |>
ss_mean(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999")
)
data |>
ss_mean(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999"),
combine = FALSE
)
data |>
ss_mean(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = NULL,
exclude = NULL,
events = c("ses-00A", "ses-01A"),
)
Compute mean for MH-PLE scores
Description
Calculates mean scores for variables with forking logic, where variables may only be applicable based on certain conditions. Missing values and exclusions are handled based on the forking variable values.
Usage
ss_mean_mh_ple(
data,
name,
fork_vars,
fork_val = "1",
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
combine = TRUE,
no_na = FALSE
)
Arguments
data |
Data frame containing columns to summarize |
name |
String specifying name for summary score column |
fork_vars |
Character vector of columns used as logical conditions |
fork_val |
String indicating value in fork_vars for valid responses |
vars |
Character vector of columns to summarize |
max_na |
Integer for maximum allowed missing values |
exclude |
Character vector of values to exclude |
events |
Character vector of events to compute scores for |
combine |
Logical; if TRUE, append score to input data |
no_na |
Logical; if TRUE, return NA when any value is missing |
Value
Data frame with summary score column
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~a__severe, ~b__severe, ~c__severe,
"ses-00A", "1", "1", "1", "1", NA, NA,
"ses-01A", "1", "1", "1", "2", "777", "2"
)
data |>
ss_mean_mh_ple(
name = "mean",
fork_vars = c("a", "b", "c"),
vars = paste0(c("a", "b", "c"), "__severe"),
max_na = 1,
exclude = c("777", "999")
)
Compute mean of positive values
Description
Computes the mean of strictly positive values for a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
Usage
ss_mean_pos(
data,
name,
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~d, ~e,
"ses-00A", -1, 1, 1, 1, NA,
"ses-01A", 2, 777, 2, 2, 2,
"ses-02A", 3, 3, 999, 3, 3,
"ses-02A", 4, 4, 4, 777, NA,
"ses-03A", 5, NA, 777, 999, 5,
"ses-03A", NA, NA, NA, NA, NA,
"ses-04A", 1, NA, NA, NA, NA
)
data |>
ss_mean_pos(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999")
)
data |>
ss_mean_pos(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999"),
combine = FALSE
)
data |>
ss_mean_pos(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = NULL,
exclude = NULL,
events = c("ses-00A", "ses-01A"),
)
Compute number missing
Description
Computes the number of missing items among a set of variables, with the option to exclude certain values (for non-responses like "Don't know" / "Decline to answer"). If all items are NA, the summary score will not be computed (assuming that the questionnaire was not filled out at all).
Usage
ss_nm(data, name, vars, exclude = NULL, events = NULL, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~d, ~e,
"ses-00A", 1, 1, 1, 1, NA,
"ses-01A", 2, 777, 2, 2, 2,
"ses-02A", 3, 3, 999, 3, 3,
"ses-02A", 4, 4, 4, 777, NA,
"ses-03A", 5, NA, 777, 999, 5,
"ses-03A", NA, NA, NA, NA, NA,
"ses-04A", 1, NA, NA, NA, NA
)
data |>
ss_nm(
name = "nm",
vars = c("a", "b", "c", "d", "e"),
exclude = c("777", "999")
)
data |>
ss_nm(
name = "nm",
vars = c("a", "b", "c", "d", "e"),
exclude = c("777", "999"),
event = c("ses-00A", "ses-01A")
)
Count missing values for MH-PLE scores
Description
Counts missing values for variables with forking logic, where variables may only be applicable based on certain conditions. Excluded values are treated as missing.
Usage
ss_nm_mh_ple(
data,
name,
fork_vars,
fork_val = "1",
vars,
exclude = NULL,
events = NULL,
combine = TRUE
)
Arguments
data |
Data frame containing columns to summarize |
name |
String specifying name for summary score column |
fork_vars |
Character vector of columns used as logical conditions |
fork_val |
String indicating value in fork_vars for valid responses |
vars |
Character vector of columns to summarize |
exclude |
Character vector of values to exclude |
events |
Character vector of events to compute scores for |
combine |
Logical; if TRUE, append score to input data |
Value
Data frame with count of missing values
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~a__severe, ~b__severe, ~c__severe,
"ses-00A", "1", "1", "1", "1", NA, NA,
"ses-01A", "1", "1", "1", "2", "777", "2"
)
data |>
ss_nm_mh_ple(
name = "nm",
fork_vars = c("a", "b", "c"),
vars = paste0(c("a", "b", "c"), "__severe"),
exclude = c("777", "999")
)
Compute pro-rated sum
Description
Computes the pro-rated sum of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values. Also include a second field
Usage
ss_prsum(
data,
name,
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
as_integer = TRUE,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
as_integer |
logical. Whether to coerce the summary score to an integer,
default is |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tibble(
participant_id = c("A", "A", "A", "B", "A", "B", "A"),
session_id = c("ses-00A", "ses-01A", "ses-02A", "ses-02A", "ses-03A", "0ses-3A", "ses-04A"),
a = c(1, 2, 3, 4, 5, NA, 1),
b = c(1, 777, 3, 4, NA, NA, NA),
c = c(1, 2, 999, 4, 777, NA, NA),
d = c(1, 2, 3, 777, 999, NA, NA),
e = c(NA, 2, 3, NA, 5, NA, NA)
)
data |>
ss_prsum(
name = "score_prorated_sum",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999")
)
data |>
ss_prsum(
name = "score_prorated_sum",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999"),
combine = FALSE
)
data |>
ss_prsum(
name = "score_prorated_sum",
vars = c("a", "b", "c", "d", "e"),
max_na = NULL,
exclude = NULL,
events = c("ses-00A", "ses-01A"),
)
Compute sum
Description
Computes the sum of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
Usage
ss_sum(
data,
name,
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
as_integer = TRUE,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
as_integer |
logical. Whether to coerce the summary score to an integer,
default is |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~d, ~e,
"ses-00A", 1, 1, 1, 1, NA,
"ses-01A", 2, 777, 2, 2, 2,
"ses-02A", 3, 3, 999, 3, 3,
"ses-02A", 4, 4, 4, 777, NA,
"ses-03A", 5, NA, 777, 999, 5,
"ses-03A", NA, NA, NA, NA, NA,
"ses-04A", 1, NA, NA, NA, NA
)
data |>
ss_sum(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999")
)
data |>
ss_sum(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = 1,
exclude = c("777", "999"),
combine = FALSE
)
data |>
ss_sum(
name = "mean",
vars = c("a", "b", "c", "d", "e"),
max_na = NULL,
exclude = NULL,
events = c("ses-00A", "ses-01A"),
)
Compute sum for MH-PLE scores
Description
Calculates sum scores for variables with forking logic, where variables may only be applicable based on certain conditions. Missing values and exclusions are handled based on the forking variable values.
Usage
ss_sum_mh_ple(
data,
name,
fork_vars,
fork_val = "1",
vars,
max_na = NULL,
exclude = NULL,
events = NULL,
combine = TRUE,
no_na = FALSE
)
Arguments
data |
Data frame containing columns to summarize |
name |
String specifying name for summary score column |
fork_vars |
Character vector of columns used as logical conditions |
fork_val |
String indicating value in fork_vars for valid responses |
vars |
Character vector of columns to summarize |
max_na |
Integer for maximum allowed missing values |
exclude |
Character vector of values to exclude |
events |
Character vector of events to compute scores for |
combine |
Logical; if TRUE, append score to input data |
no_na |
Logical; if TRUE, return NA when any value is missing |
Value
Data frame with summary score column
Examples
data <- tibble::tribble(
~session_id, ~a, ~b, ~c, ~a__severe, ~b__severe, ~c__severe,
"ses-00A", "1", "1", "1", "1", NA, NA,
"ses-01A", "1", "1", "1", "2", "777", "2"
)
data |>
ss_sum_mh_ple(
name = "sum",
fork_vars = c("a", "b", "c"),
vars = paste0(c("a", "b", "c"), "__severe"),
max_na = 1,
exclude = c("777", "999")
)
Compute T-score
Description
This function computes the T-score based on the given columns, and the provided T-score table.
Usage
ss_tscore(
data,
data_norm = NULL,
vars,
name = "tscore",
max_na = NULL,
exclude = NULL,
col_age = "age",
col_sex = "sex",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the T-score table. See details. |
vars |
character vector. The names of the columns to be summarized. |
name |
character. The column name of the T-score. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
col_age |
character. The name of the age column. |
col_sex |
character The name of sex column. |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
Details
T-score table
The data_norm
should be a data frame containing the T-score table. The
default value NULL
is only used for internal usage (see below). For normal
usage, the data_norm
should be provided.
The table should have the following columns:
-
sex
: character or factor both ok. The biological sex of the participant. The values should be either "1" (male) or "2" (female). -
age_min
: numeric. The minimum age of the participant. -
age_max
: numeric. The maximum age of the participant. -
scale_r
: numeric. The raw score of the scale. -
scale_t
: numeric. The T-score of the scale.
For example
A tibble: n x 5
sex | age_min | age_max | scale_r | scale_t |
<chr> | <dbl> | <dbl> | <dbl> | <dbl> |
1 | 18 | 35 | 50 | 1 |
1 | 18 | 35 | 50.5 | 2 |
1 | 18 | 35 | 51 | 3 |
1 | 18 | 35 | 51.5 | 4 |
... | ||||
out-range values
If the age of the participant is out of the range of the T-score table, the function will return
NA
.If the raw score is out of the range of the T-score table, the function will return
NA
.If any of the
sex
column is not "1" or "2", the function will returnNA
.If any of the required columns has
NA
, that row will returnNA
.
Internal usage
When used in DSM internally, the data_norm
can be omitted. Instead, the
function will try to find the T-score table from the list_tscore
option,
and tries to find the tscore list based on object name provided in the
list_tscore
option. Once the object is found, the function will automatically
extract the T-score table based on the function name.
The
list_tscore
object should present in the global environment.See
get_tscore_tbl()
for more details on how to construct thelist_tscore
.
For example
my_tscore <<- readRDS("aseba_tscore.rds") options(list_tscore = "my_tscore") compute_mh_x_yyyy_zz_tscore(data)
Value
tbl. The input data frame with the T-score appended as a new column
if combine
is TRUE, otherwise only the T-score column.
Examples
data_norm <- tibble::tibble(
sex = c("1", "1", "1", "1", "1"),
age_min = 18,
age_max = 35,
scale_r = 0:4,
scale_t = 20:24
)
data <- tibble::tibble(
var1 = c(0, 1, NA, 1, 2),
var2 = c(1, 2, 1, 2, 5),
age = c(18, 20, 25, 99, 35),
sex = c("1", "1", "1", "1", "1")
)
ss_tscore(
data = data,
data_norm = data_norm,
max_na = 0,
vars = c("var1", "var2")
)
Configuration for Substance Use Interview calculations
Description
Settings for processing SUI substance use data.
Usage
sui_config
Format
An object of class tbl_df
(inherits from tbl
, data.frame
) with 100 rows and 5 columns.
Compute age of onset use for a given substance
Description
Computes the age (in years) of onset use of a given substance.
Returns NA
for the participants with no onset use of the provided
substance reported.
Usage
sui_substances
compute_su_y_sui__onset_useage(data, name, substance, combine = TRUE)
Arguments
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
Format
sui_substances
is a character vector of substances keywords.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_su_y_sui__onset_useage(
data = data_sui,
name = "su_y_sui__alc__onset_useage",
substance = "alc"
)
## End(Not run)
Configuration for Timeline Followback calculations
Description
Settings for processing TLFB substance use data.
Usage
tlfb_config
Format
An object of class tbl_df
(inherits from tbl
, data.frame
) with 870 rows and 10 columns.
Compute TLFB length of abstinence
Description
Computes the length of abstinence in days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; and/or only binge use.
Usage
tlfb_substances
compute_tlfb_abst(
data,
name,
substance = NULL,
period = NULL,
days = NULL,
binge = NULL
)
Arguments
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
Format
tlfb_substances
is a character vector of all substances that can be
reported in the TLFB.
Value
A tibble with the computed score for each participant/event.
Examples
## Not run:
compute_tlfb_abst(
data = data_tlfb,
name = "su_y_tlfb__alc__cum_abst",
substance = "Alcohol"
)
## End(Not run)
Compute "Cohort description: Highest education across caregivers"
Description
Computes the summary score ab_g_dyn__cohort_edu__cgs
Cohort description: Highest education across caregivers
-
Summarized variables:
-
ab_p_demo__edu__slf_001
-
ab_p_demo__edu__slf_001__v01
-
ab_p_demo__edu__slf_001__v02
-
ab_p_demo__edu__prtnr_001
-
ab_p_demo__edu__prtnr_001__v01
-
-
Excluded values:
777
999
Usage
vars_ab_g_dyn__cohort_edu__cgs
compute_ab_g_dyn__cohort_edu__cgs(
data,
name = "ab_g_dyn__cohort_edu__cgs",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
Format
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_edu__cgs
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Cohort description: Household income - 6 levels"
Description
Computes the summary score ab_g_dyn__cohort_income__hhold__6lvl
Cohort description: Household income - 6 levels
-
Summarized variables:
-
ab_p_demo__income__hhold_001
-
ab_p_demo__income__hhold_001__v01
-
Usage
vars_ab_g_dyn__cohort_income__hhold__6lvl
compute_ab_g_dyn__cohort_income__hhold__6lvl(
data,
name = "ab_g_dyn__cohort_income__hhold__6lvl",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_income__hhold__6lvl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Cohort description: Caregivers' partnership and employment status"
Description
Computes the summary score ab_g_dyn__cohort_prtnrshp__employ
Cohort description: Caregivers' partnership and employment status
-
Summarized variables:
-
ab_p_demo__marital__slf_001
-
ab_p_demo__prtnr_001
-
ab_p_demo__empl__slf_001
-
ab_p_demo__empl__prtnr_001
-
ab_p_demo__empl__prtnr_001__v01
-
-
Excluded values:
777
999
Usage
vars_ab_g_dyn__cohort_prtnrshp__employ
compute_ab_g_dyn__cohort_prtnrshp__employ(
data,
name = "ab_g_dyn__cohort_prtnrshp__employ",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_prtnrshp__employ
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Cohort description: Ethnicity (Hispanic or not Hispanic) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_ethn
Cohort description: Ethnicity (Hispanic or not Hispanic) [Based on
baseline response; missingness filled in from longitudinal responses]
-
Summarized variables:
-
ab_p_demo__ethn_001
-
ab_p_demo__ethn_001__v01
-
-
Excluded values:
777
999
-
Notes:
Values in
ab_p_demo__ethn_001__v01
were recoded:"0" –> "2",
"2" –> "1"
"3" –> "1"
"4" –> "1"
Values in
ab_p_demo__ethn_001
were recoded:"0" –> "2"
Usage
vars_ab_g_stc__cohort_ethn
compute_ab_g_stc__cohort_ethn(
data,
name = "ab_g_stc__cohort_ethn",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
Format
a character vector of all column names
used to compute summary score of ab_g_stc__cohort_ethn
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Cohort description: Ethno-racial identity (Legacy ABCD variable reporting 6 levels; Hispanic ethnicity report outweighs any racial endorements) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_ethnrace__leg
Cohort description: Ethno-racial identity (Legacy ABCD variable
reporting 6 levels; Hispanic ethnicity report outweighs any racial
endorements) [Based on baseline response; missingness filled in from
longitudinal responses]
-
Summarized variables:
-
ab_p_demo__ethn_001
-
ab_p_demo__ethn_001__v01
-
ab_p_demo__race_001___0
-
ab_p_demo__race_001___10
-
ab_p_demo__race_001___11
-
ab_p_demo__race_001___12
-
ab_p_demo__race_001___13
-
ab_p_demo__race_001___14
-
ab_p_demo__race_001___15
-
ab_p_demo__race_001___16
-
ab_p_demo__race_001___17
-
ab_p_demo__race_001___18
-
ab_p_demo__race_001___19
-
ab_p_demo__race_001___20
-
ab_p_demo__race_001___21
-
ab_p_demo__race_001___22
-
ab_p_demo__race_001___23
-
ab_p_demo__race_001___24
-
ab_p_demo__race_001___25
-
ab_p_demo__race_001___777
-
ab_p_demo__race_001___999
-
ab_p_demo__race_001__v01___999
-
ab_p_demo__race_001__v01___10
-
ab_p_demo__race_001__v01___11
-
ab_p_demo__race_001__v01___12
-
ab_p_demo__race_001__v01___20
-
ab_p_demo__race_001__v01___21
-
ab_p_demo__race_001__v01___22
-
ab_p_demo__race_001__v01___23
-
ab_p_demo__race_001__v01___13
-
ab_p_demo__race_001__v01___14
-
ab_p_demo__race_001__v01___15
-
ab_p_demo__race_001__v01___17
-
ab_p_demo__race_001__v01___18
-
ab_p_demo__race_001__v01___19
-
ab_p_demo__race_001__v01___16
-
ab_p_demo__race_001__v01___24
-
ab_p_demo__race_001__v01___777
-
Usage
vars_ab_g_stc__cohort_ethnrace__leg
compute_ab_g_stc__cohort_ethnrace__leg(
data,
name = "ab_g_stc__cohort_ethnrace__leg",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a character vector of all column names
used to compute summary score of ab_g_stc__cohort_ethnrace__leg
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Cohort description: Ethno-racial identity (8 level aggregation providing information on Black identity for multiracial endorements) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_ethnrace__mblack
Cohort description: Ethno-racial identity (8 level aggregation providing
information on Black identity for multiracial endorements) [Based on
baseline response; missingness filled in from longitudinal responses]
-
Summarized variables:
-
ab_p_demo__ethn_001
-
ab_p_demo__ethn_001__v01
-
ab_p_demo__race_001___0
-
ab_p_demo__race_001___10
-
ab_p_demo__race_001___11
-
ab_p_demo__race_001___12
-
ab_p_demo__race_001___13
-
ab_p_demo__race_001___14
-
ab_p_demo__race_001___15
-
ab_p_demo__race_001___16
-
ab_p_demo__race_001___17
-
ab_p_demo__race_001___18
-
ab_p_demo__race_001___19
-
ab_p_demo__race_001___20
-
ab_p_demo__race_001___21
-
ab_p_demo__race_001___22
-
ab_p_demo__race_001___23
-
ab_p_demo__race_001___24
-
ab_p_demo__race_001___25
-
ab_p_demo__race_001___777
-
ab_p_demo__race_001___999
-
ab_p_demo__race_001__v01___999
-
ab_p_demo__race_001__v01___10
-
ab_p_demo__race_001__v01___11
-
ab_p_demo__race_001__v01___12
-
ab_p_demo__race_001__v01___20
-
ab_p_demo__race_001__v01___21
-
ab_p_demo__race_001__v01___22
-
ab_p_demo__race_001__v01___23
-
ab_p_demo__race_001__v01___13
-
ab_p_demo__race_001__v01___14
-
ab_p_demo__race_001__v01___15
-
ab_p_demo__race_001__v01___17
-
ab_p_demo__race_001__v01___18
-
ab_p_demo__race_001__v01___19
-
ab_p_demo__race_001__v01___16
-
ab_p_demo__race_001__v01___24
-
ab_p_demo__race_001__v01___777
-
Usage
vars_ab_g_stc__cohort_ethnrace__mblack
compute_ab_g_stc__cohort_ethnrace__mblack(
data,
name = "ab_g_stc__cohort_ethnrace__mblack",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__mblack
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Cohort description: Ethno-racial identity (15 level classification from fc_p_meim_001) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_ethnrace__meim
Cohort description: Ethno-racial identity (15 level classification from
fc_p_meim_001) [Based on baseline response; missingness filled in from
longitudinal responses]
-
Summarized variables:
-
fc_p_meim_001
-
-
Excluded values:
777
999
Usage
vars_ab_g_stc__cohort_ethnrace__meim
compute_ab_g_stc__cohort_ethnrace__meim(
data,
name = "ab_g_stc__cohort_ethnrace__meim",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
Format
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__meim
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Cohort description: Ethno-racial identity (8 level aggregation providing information on ethnicity for multiracial endorements) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_ethnrace__mhisp
Cohort description: Ethno-racial identity (8 level aggregation providing
information on ethnicity for multiracial endorements) [Based on baseline
response; missingness filled in from longitudinal responses]
-
Summarized variables:
-
ab_p_demo__ethn_001
-
ab_p_demo__ethn_001__v01
-
ab_p_demo__race_001___0
-
ab_p_demo__race_001___10
-
ab_p_demo__race_001___11
-
ab_p_demo__race_001___12
-
ab_p_demo__race_001___13
-
ab_p_demo__race_001___14
-
ab_p_demo__race_001___15
-
ab_p_demo__race_001___16
-
ab_p_demo__race_001___17
-
ab_p_demo__race_001___18
-
ab_p_demo__race_001___19
-
ab_p_demo__race_001___20
-
ab_p_demo__race_001___21
-
ab_p_demo__race_001___22
-
ab_p_demo__race_001___23
-
ab_p_demo__race_001___24
-
ab_p_demo__race_001___25
-
ab_p_demo__race_001___777
-
ab_p_demo__race_001___999
-
ab_p_demo__race_001__v01___999
-
ab_p_demo__race_001__v01___10
-
ab_p_demo__race_001__v01___11
-
ab_p_demo__race_001__v01___12
-
ab_p_demo__race_001__v01___20
-
ab_p_demo__race_001__v01___21
-
ab_p_demo__race_001__v01___22
-
ab_p_demo__race_001__v01___23
-
ab_p_demo__race_001__v01___13
-
ab_p_demo__race_001__v01___14
-
ab_p_demo__race_001__v01___15
-
ab_p_demo__race_001__v01___17
-
ab_p_demo__race_001__v01___18
-
ab_p_demo__race_001__v01___19
-
ab_p_demo__race_001__v01___16
-
ab_p_demo__race_001__v01___24
-
ab_p_demo__race_001__v01___777
-
Usage
vars_ab_g_stc__cohort_ethnrace__mhisp
compute_ab_g_stc__cohort_ethnrace__mhisp(
data,
name = "ab_g_stc__cohort_ethnrace__mhisp",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__mhisp
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Cohort description: Race (NIH classification reporting 7 levels) [Based on baseline response; missingness filled in from longitudinal responses]"
Description
Computes the summary score ab_g_stc__cohort_race__nih
Cohort description: Race (NIH classification reporting 7 levels) [Based
on baseline response; missingness filled in from longitudinal responses]
-
Summarized variables:
-
ab_p_demo__race_001___0
-
ab_p_demo__race_001___10
-
ab_p_demo__race_001___11
-
ab_p_demo__race_001___12
-
ab_p_demo__race_001___13
-
ab_p_demo__race_001___14
-
ab_p_demo__race_001___15
-
ab_p_demo__race_001___16
-
ab_p_demo__race_001___17
-
ab_p_demo__race_001___18
-
ab_p_demo__race_001___19
-
ab_p_demo__race_001___20
-
ab_p_demo__race_001___21
-
ab_p_demo__race_001___22
-
ab_p_demo__race_001___23
-
ab_p_demo__race_001___24
-
ab_p_demo__race_001___25
-
ab_p_demo__race_001___777
-
ab_p_demo__race_001___999
-
ab_p_demo__race_001__v01___999
-
ab_p_demo__race_001__v01___10
-
ab_p_demo__race_001__v01___11
-
ab_p_demo__race_001__v01___12
-
ab_p_demo__race_001__v01___20
-
ab_p_demo__race_001__v01___21
-
ab_p_demo__race_001__v01___22
-
ab_p_demo__race_001__v01___23
-
ab_p_demo__race_001__v01___13
-
ab_p_demo__race_001__v01___14
-
ab_p_demo__race_001__v01___15
-
ab_p_demo__race_001__v01___17
-
ab_p_demo__race_001__v01___18
-
ab_p_demo__race_001__v01___19
-
ab_p_demo__race_001__v01___16
-
ab_p_demo__race_001__v01___24
-
ab_p_demo__race_001__v01___777
-
Usage
vars_ab_g_stc__cohort_race__nih
compute_ab_g_stc__cohort_race__nih(
data,
name = "ab_g_stc__cohort_race__nih",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
a tibble of all column names, baseline and longitudinal,
used to compute summary score of ab_g_stc__cohort_race__nih
.
Value
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE
, a data frame with two
columns: participant ID and summary score.
Compute "Family Environment Scale [Parent] (Cohesion): Mean"
Description
Computes the summary score fc_p_fes__cohes_mean
(Family Environment Scale [Parent] (Cohesion): Mean)
-
Summarized variables:
-
fc_p_fes__cohes_001
-
fc_p_fes__cohes_002
-
fc_p_fes__cohes_003
-
fc_p_fes__cohes_004
-
fc_p_fes__cohes_005
-
fc_p_fes__cohes_006
-
fc_p_fes__cohes_007
-
fc_p_fes__cohes_008
-
fc_p_fes__cohes_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__cohes
compute_fc_p_fes__cohes_mean(
data,
name = "fc_p_fes__cohes_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__cohes is a character vector of all column names
used to compute summary score of fc_p_fes__cohes
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Parent] (Conflict): Mean"
Description
Computes the summary score fc_p_fes__confl_mean
(Family Environment Scale [Parent] (Conflict): Mean)
-
Summarized variables:
-
fc_p_fes__confl_001
-
fc_p_fes__confl_002
-
fc_p_fes__confl_003
-
fc_p_fes__confl_004
-
fc_p_fes__confl_005
-
fc_p_fes__confl_006
-
fc_p_fes__confl_007
-
fc_p_fes__confl_008
-
fc_p_fes__confl_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__confl
compute_fc_p_fes__confl_mean(
data,
name = "fc_p_fes__confl_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__confl is a character vector of all column names
used to compute summary score of fc_p_fes__confl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Parent] (Expression): Mean"
Description
Computes the summary score fc_p_fes__expr_mean
(Family Environment Scale [Parent] (Expression): Mean)
-
Summarized variables:
-
fc_p_fes__expr_001
-
fc_p_fes__expr_002
-
fc_p_fes__expr_003
-
fc_p_fes__expr_004
-
fc_p_fes__expr_005
-
fc_p_fes__expr_006
-
fc_p_fes__expr_007
-
fc_p_fes__expr_008
-
fc_p_fes__expr_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__expr
compute_fc_p_fes__expr_mean(
data,
name = "fc_p_fes__expr_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__expr is a character vector of all column names
used to compute summary score of fc_p_fes__expr
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Parent] (Intellectual and cultural): Mean"
Description
Computes the summary score fc_p_fes__intelcult_mean
(Family Environment Scale [Parent] (Intellectual and cultural): Mean)
-
Summarized variables:
-
fc_p_fes__intelcult_001
-
fc_p_fes__intelcult_002
-
fc_p_fes__intelcult_003
-
fc_p_fes__intelcult_004
-
fc_p_fes__intelcult_005
-
fc_p_fes__intelcult_006
-
fc_p_fes__intelcult_007
-
fc_p_fes__intelcult_008
-
fc_p_fes__intelcult_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__intelcult
compute_fc_p_fes__intelcult_mean(
data,
name = "fc_p_fes__intelcult_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__intelcult is a character vector of all column names
used to compute summary score of fc_p_fes__intelcult
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Parent] (Organization): Mean"
Description
Computes the summary score fc_p_fes__org_mean
(Family Environment Scale [Parent] (Organization): Mean)
-
Summarized variables:
-
fc_p_fes__org_001
-
fc_p_fes__org_002
-
fc_p_fes__org_003
-
fc_p_fes__org_004
-
fc_p_fes__org_005
-
fc_p_fes__org_006
-
fc_p_fes__org_007
-
fc_p_fes__org_008
-
fc_p_fes__org_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__org
compute_fc_p_fes__org_mean(
data,
name = "fc_p_fes__org_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__org is a character vector of all column names
used to compute summary score of fc_p_fes__org
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Parent] (Activity and recreational): Mean"
Description
Computes the summary score fc_p_fes__rec_mean
(Family Environment Scale [Parent] (Activity and recreational): Mean)
-
Summarized variables:
-
fc_p_fes__rec_001
-
fc_p_fes__rec_002
-
fc_p_fes__rec_003
-
fc_p_fes__rec_004
-
fc_p_fes__rec_005
-
fc_p_fes__rec_006
-
fc_p_fes__rec_007
-
fc_p_fes__rec_008
-
fc_p_fes__rec_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_p_fes__rec
compute_fc_p_fes__rec_mean(
data,
name = "fc_p_fes__rec_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_fes__rec is a character vector of all column names
used to compute summary score of fc_p_fes__rec
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent]: Mean"
Description
Computes the summary score fc_p_meim_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent]: Mean)
-
Summarized variables:
-
fc_p_meim__commattach_001
-
fc_p_meim__commattach_002
-
fc_p_meim__commattach_003
-
fc_p_meim__explor_001
-
fc_p_meim__explor_002
-
fc_p_meim__explor_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_p_meim
compute_fc_p_meim_mean(
data,
name = "fc_p_meim_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_meim is a character vector of all column names
used to compute summary score of fc_p_meim
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and attachment): Mean"
Description
Computes the summary score fc_p_meim__commattach_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and
attachment): Mean)
-
Summarized variables:
-
fc_p_meim__commattach_001
-
fc_p_meim__commattach_002
-
fc_p_meim__commattach_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_p_meim__commattach
compute_fc_p_meim__commattach_mean(
data,
name = "fc_p_meim__commattach_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_p_meim__commattach is a character vector of all column names
used to compute summary score of fc_p_meim__commattach
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration): Mean"
Description
Computes the summary score fc_p_meim__explor_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration): Mean)
-
Summarized variables:
-
fc_p_meim__explor_001
-
fc_p_meim__explor_002
-
fc_p_meim__explor_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_p_meim__explor
compute_fc_p_meim__explor_mean(
data,
name = "fc_p_meim__explor_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_p_meim__explor is a character vector of all column names
used to compute summary score of fc_p_meim__explor
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Neighborhood Collective Efficacy [Parent]: Mean"
Description
Computes the summary score fc_p_nce_mean
(Neighborhood Collective Efficacy [Parent]: Mean)
-
Summarized variables:
-
fc_p_nce__cc_001
-
fc_p_nce__cc_002
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
fc_p_nce__cc_005
-
fc_p_nce__isc_001
-
fc_p_nce__isc_002
-
fc_p_nce__isc_003
-
fc_p_nce__isc_004
-
fc_p_nce__isc_005
-
-
Excluded values:
777
-
Validation criterion: maximally 2 of 10 items missing
-
Notes:
The following variables are reverse coded before computing the summary score:
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
The value "99" (Don't know) is recoded to "3" (Neither... nor...)
Usage
vars_fc_p_nce
compute_fc_p_nce_mean(data, name = "fc_p_nce_mean", max_na = 2, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 2). |
combine |
logical. If |
Format
vars_fc_p_nce is a character vector of all column names
used to compute summary score of fc_p_nce
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Neighborhood Collective Efficacy [Parent] (Community cohesion): Mean"
Description
Computes the summary score fc_p_nce__cc_mean
(Neighborhood Collective Efficacy [Parent] (Community cohesion): Mean)
-
Summarized variables:
-
fc_p_nce__cc_001
-
fc_p_nce__cc_002
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
fc_p_nce__cc_005
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 5 items missing
-
Notes:
The following variables are reverse coded before computing the summary score:
-
fc_p_nce__cc_003
-
fc_p_nce__cc_004
-
The value "99" (Don't know) is recoded to "3" (Neither... nor...)
Usage
vars_fc_p_nce__cc
compute_fc_p_nce__cc_mean(
data,
name = "fc_p_nce__cc_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_nce__cc is a character vector of all column names
used to compute summary score of fc_p_nce__cc
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Neighborhood Collective Efficacy [Parent] (Informal social control): Mean"
Description
Computes the summary score fc_p_nce__isc_mean
(Neighborhood Collective Efficacy [Parent] (Informal social control): Mean)
-
Summarized variables:
-
fc_p_nce__isc_001
-
fc_p_nce__isc_002
-
fc_p_nce__isc_003
-
fc_p_nce__isc_004
-
fc_p_nce__isc_005
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 5 items missing
-
Note: The value "99" (Don't know) is recoded to "3" (Neither... nor...)
Usage
vars_fc_p_nce__isc
compute_fc_p_nce__isc_mean(
data,
name = "fc_p_nce__isc_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_nce__isc is a character vector of all column names
used to compute summary score of fc_p_nce__isc
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Neighborhood Safety & Crime [Parent] (Neighborhood safety): Mean"
Description
Computes the summary score fc_p_nsc__ns_mean
(Neighborhood Safety & Crime [Parent] (Neighborhood safety): Mean)
-
Summarized variables:
-
fc_p_nsc__ns_001
-
fc_p_nsc__ns_002
-
fc_p_nsc__ns_003
-
-
Excluded values:
777
999
-
Validation criterion: none of 3 items missing
Usage
vars_fc_p_nsc__ns
compute_fc_p_nsc__ns_mean(
data,
name = "fc_p_nsc__ns_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_p_nsc__ns is a character vector of all column names
used to compute summary score of fc_p_nsc__ns
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Parental Knowledge Scale [Parent]: Mean"
Description
Computes the summary score fc_p_pk__knowl_mean
(Parental Knowledge Scale [Parent]: Mean)
-
Summarized variables:
-
fc_p_pk__knowl_001
-
fc_p_pk__knowl_002
-
fc_p_pk__knowl_003
-
fc_p_pk__knowl_004
-
fc_p_pk__knowl_005
-
fc_p_pk__knowl_006
-
fc_p_pk__knowl_007
-
fc_p_pk__knowl_008
-
fc_p_pk__knowl_009
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 9 items missing
-
Notes: All items are reverse coded before computing the summary score.
Usage
vars_fc_p_pk__knowl
compute_fc_p_pk__knowl_mean(
data,
name = "fc_p_pk__knowl_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_pk__knowl is a character vector of all column names
used to compute summary score of fc_p_pk__knowl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Prosocial Behavior [Parent]: Mean"
Description
Computes the summary score fc_p_psb_mean
(Prosocial Behavior [Parent]: Mean)
-
Summarized variables:
-
fc_p_psb_001
-
fc_p_psb_002
-
fc_p_psb_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_p_psb
compute_fc_p_psb_mean(data, name = "fc_p_psb_mean", max_na = 0, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_p_psb is a character vector of all column names
used to compute summary score of fc_p_psb
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Parent] (Independence and self-reliance): Mean"
Description
Computes the summary score fc_p_vs__indselfrel_mean
(Values Scale [Parent] (Independence and
self-reliance): Mean)
-
Summarized variables:
-
fc_p_vs__indselfrel_001
-
fc_p_vs__indselfrel_002
-
fc_p_vs__indselfrel_003
-
fc_p_vs__indselfrel_004
-
fc_p_vs__indselfrel_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_p_vs__indselfrel
compute_fc_p_vs__indselfrel_mean(
data,
name = "fc_p_vs__indselfrel_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_vs__indselfrel is a character vector of all column names
used to compute summary score of fc_p_vs__indselfrel
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Parent] (Family obligation): Mean"
Description
Computes the summary score fc_p_vs__obl_mean
(Values Scale [Parent] (Family obligation): Mean)
-
Summarized variables:
-
fc_p_vs__obl_001
-
fc_p_vs__obl_002
-
fc_p_vs__obl_003
-
fc_p_vs__obl_004
-
fc_p_vs__obl_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_p_vs__obl
compute_fc_p_vs__obl_mean(
data,
name = "fc_p_vs__obl_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_vs__obl is a character vector of all column names
used to compute summary score of fc_p_vs__obl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Parent] (Family as referent): Mean"
Description
Computes the summary score fc_p_vs__ref_mean
(Values Scale [Parent] (Family as referent): Mean)
-
Summarized variables:
-
fc_p_vs__ref_001
-
fc_p_vs__ref_002
-
fc_p_vs__ref_003
-
fc_p_vs__ref_004
-
fc_p_vs__ref_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_p_vs__ref
compute_fc_p_vs__ref_mean(
data,
name = "fc_p_vs__ref_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_vs__ref is a character vector of all column names
used to compute summary score of fc_p_vs__ref
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Parent] (Religion): Mean"
Description
Computes the summary score fc_p_vs__relig_mean
(Values Scale [Parent] (Religion): Mean)
-
Summarized variables:
-
fc_p_vs__relig_001
-
fc_p_vs__relig_002
-
fc_p_vs__relig_003
-
fc_p_vs__relig_004
-
fc_p_vs__relig_005
-
fc_p_vs__relig_006
-
fc_p_vs__relig_007
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 7 items missing
Usage
vars_fc_p_vs__relig
compute_fc_p_vs__relig_mean(
data,
name = "fc_p_vs__relig_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_vs__relig is a character vector of all column names
used to compute summary score of fc_p_vs__relig
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Parent] (Family support): Mean"
Description
Computes the summary score fc_p_vs__supp_mean
(Values Scale [Parent] (Family support): Mean)
-
Summarized variables:
-
fc_p_vs__supp_001
-
fc_p_vs__supp_002
-
fc_p_vs__supp_003
-
fc_p_vs__supp_004
-
fc_p_vs__supp_005
-
fc_p_vs__supp_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_p_vs__supp
compute_fc_p_vs__supp_mean(
data,
name = "fc_p_vs__supp_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_p_vs__supp is a character vector of all column names
used to compute summary score of fc_p_vs__supp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Activity Space [Youth] (Safety): Mean"
Description
Computes the summary score fc_y_as__safe_mean
(Activity Space [Youth] (Safety): Mean)
-
Summarized variables:
-
fc_y_as__safe_001a
-
fc_y_as__safe_001b
-
fc_y_as__safe_001c
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_y_as__safe
compute_fc_y_as__safe_mean(
data,
name = "fc_y_as__safe_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_as__safe is a character vector of all column names
used to compute summary score of fc_y_as__safe
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A): Mean"
Description
Computes the summary score fc_y_crpbi__cg1_mean
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A):
Mean)
-
Summarized variables:
-
fc_y_crpbi__cg1_002
-
fc_y_crpbi__cg1_003
-
fc_y_crpbi__cg1_004
-
fc_y_crpbi__cg1_005
-
fc_y_crpbi__cg1_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_crpbi__cg1
compute_fc_y_crpbi__cg1_mean(
data,
name = "fc_y_crpbi__cg1_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_crpbi__cg1 is a character vector of all column names
used to compute summary score of fc_y_crpbi__cg1
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B): Mean"
Description
Computes the summary score fc_y_crpbi__cg2_mean
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B):
Mean)
-
Summarized variables:
-
fc_y_crpbi__cg2_002
-
fc_y_crpbi__cg2_003
-
fc_y_crpbi__cg2_004
-
fc_y_crpbi__cg2_005
-
fc_y_crpbi__cg2_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_crpbi__cg2
compute_fc_y_crpbi__cg2_mean(
data,
name = "fc_y_crpbi__cg2_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_crpbi__cg2 is a character vector of all column names
used to compute summary score of fc_y_crpbi__cg2
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Experiences with Unfair Treatment [Youth] (Ethnicity): Mean"
Description
Computes the summary score fc_y_eut__ethn_mean
(Experiences with Unfair Treatment [Youth] (Ethnicity): Mean)
-
Summarized variables:
-
fc_y_eut__ethn_001a
-
fc_y_eut__ethn_001b
-
fc_y_eut__ethn_001c
/fc_y_eut__ethn_001c__v01
-
fc_y_eut__ethn_001d
(only from event "ses-06A" onwards) -
fc_y_eut__ethn_002
-
fc_y_eut__ethn_003a
/fc_y_eut__ethn_003a__v01
-
fc_y_eut__ethn_003b
/fc_y_eut__ethn_003b__v01
-
fc_y_eut__ethn_003c
/fc_y_eut__ethn_003c__v01
-
-
Excluded values:
444
777
999
-
Validation criterion:
before event ses-06A: none of 7 items missing
starting at event ses-06A: maximally 1 of 8 items missing
Usage
vars_fc_y_eut__ethn
compute_fc_y_eut__ethn_mean(data, name = "fc_y_eut__ethn_mean", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
Format
vars_fc_y_eut__ethn is a character vector of all column names
used to compute summary score of fc_y_eut__ethn
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Youth] (Cohesion): Mean"
Description
Computes the summary score fc_y_fes__cohes_mean
(Family Environment Scale [Youth] (Cohesion): Mean)
-
Summarized variables:
-
fc_y_fes__cohes_001
-
fc_y_fes__cohes_002
-
fc_y_fes__cohes_003
-
fc_y_fes__cohes_004
-
fc_y_fes__cohes_005
-
fc_y_fes__cohes_006
-
fc_y_fes__cohes_007
-
fc_y_fes__cohes_008
-
fc_y_fes__cohes_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_y_fes__cohes
compute_fc_y_fes__cohes_mean(
data,
name = "fc_y_fes__cohes_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_fes__cohes is a character vector of all column names
used to compute summary score of fc_y_fes__cohes
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Family Environment Scale [Youth] (Conflict): Mean"
Description
Computes the summary score fc_y_fes__confl_mean
(Family Environment Scale [Youth] (Conflict): Mean)
-
Summarized variables:
-
fc_y_fes__confl_001
-
fc_y_fes__confl_002
-
fc_y_fes__confl_003
-
fc_y_fes__confl_004
-
fc_y_fes__confl_005
-
fc_y_fes__confl_006
-
fc_y_fes__confl_007
-
fc_y_fes__confl_008
-
fc_y_fes__confl_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_fc_y_fes__confl
compute_fc_y_fes__confl_mean(
data,
name = "fc_y_fes__confl_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_fes__confl is a character vector of all column names
used to compute summary score of fc_y_fes__confl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth]: Mean"
Description
Computes the summary score fc_y_meim_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth]: Mean)
-
Summarized variables:
-
fc_y_meim__commattach_001
-
fc_y_meim__commattach_002
-
fc_y_meim__commattach_003
-
fc_y_meim__explor_001
-
fc_y_meim__explor_002
-
fc_y_meim__explor_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_y_meim
compute_fc_y_meim_mean(
data,
name = "fc_y_meim_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_meim is a character vector of all column names
used to compute summary score of fc_y_meim
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and attachment): Mean"
Description
Computes the summary score fc_y_meim__commattach_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and
attachment): Mean)
-
Summarized variables:
-
fc_y_meim__commattach_001
-
fc_y_meim__commattach_002
-
fc_y_meim__commattach_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_y_meim__commattach
compute_fc_y_meim__commattach_mean(
data,
name = "fc_y_meim__commattach_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_meim__commattach is a character vector of all column names
used to compute summary score of fc_y_meim__commattach
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration): Mean"
Description
Computes the summary score fc_y_meim__explor_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration): Mean)
-
Summarized variables:
-
fc_y_meim__explor_001
-
fc_y_meim__explor_002
-
fc_y_meim__explor_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_y_meim__explor
compute_fc_y_meim__explor_mean(
data,
name = "fc_y_meim__explor_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_meim__explor is a character vector of all column names
used to compute summary score of fc_y_meim__explor
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Multidimensional Neglectful Behavior Scale [Youth]: Mean"
Description
Computes the summary score fc_y_mnbs_mean
(Multidimensional Neglectful Behavior Scale [Youth]: Mean)
-
Summarized variables:
-
fc_y_mnbs__edusupp_001
-
fc_y_mnbs__edusupp_002
-
fc_y_mnbs__edusupp_003
-
fc_y_mnbs__superv_001
-
fc_y_mnbs__superv_002
-
fc_y_mnbs__superv_003
-
fc_y_mnbs__superv_004
-
fc_y_mnbs__superv_005
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 8 items missing
Usage
vars_fc_y_mnbs
compute_fc_y_mnbs_mean(
data,
name = "fc_y_mnbs_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_mnbs is a character vector of all column names
used to compute summary score of fc_y_mnbs
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Multidimensional Neglectful Behavior Scale [Youth] (Education support): Mean"
Description
Computes the summary score fc_y_mnbs__edusupp_mean
(Multidimensional Neglectful Behavior Scale [Youth] (Education support):
Mean)
-
Summarized variables:
-
fc_y_mnbs__edusupp_001
-
fc_y_mnbs__edusupp_002
-
fc_y_mnbs__edusupp_003
-
-
Excluded values:
777
-
Validation criterion: none of 3 items missing
Usage
vars_fc_y_mnbs__edusupp
compute_fc_y_mnbs__edusupp_mean(
data,
name = "fc_y_mnbs__edusupp_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_mnbs__edusupp is a character vector of all column names
used to compute summary score of fc_y_mnbs__edusupp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Mean"
Description
Computes the summary score fc_y_mnbs__superv_mean
(Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Mean)
-
Summarized variables:
-
fc_y_mnbs__superv_001
-
fc_y_mnbs__superv_002
-
fc_y_mnbs__superv_003
-
fc_y_mnbs__superv_004
-
fc_y_mnbs__superv_005
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_mnbs__superv
compute_fc_y_mnbs__superv_mean(
data,
name = "fc_y_mnbs__superv_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_mnbs__superv is a character vector of all column names
used to compute summary score of fc_y_mnbs__superv
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Parental Monitoring [Youth]: Mean"
Description
Computes the summary score fc_y_pm_mean
(Parental Monitoring [Youth]: Mean)
-
Summarized variables:
-
fc_y_pm_001
-
fc_y_pm_002
-
fc_y_pm_003
-
fc_y_pm_004
-
fc_y_pm_005
-
-
Excluded values:
777
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_pm
compute_fc_y_pm_mean(data, name = "fc_y_pm_mean", max_na = 1, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_pm is a character vector of all column names
used to compute summary score of fc_y_pm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Peer Network Health [Youth]: Sum"
Description
Computes the summary score fc_y_pnh_sum
(Peer Network Health [Youth]: Sum)
-
Summarized variables:
-
fc_y_pnh_001
-
fc_y_pnh_002
-
fc_y_pnh_002__01
-
fc_y_pnh_003
-
fc_y_pnh_003__01
-
-
Excluded values: none
-
Validation criterion: none of 5 items missing
-
Notes:
-
fc_y_pnh_001
is scored: No = 0; Yes = 3 -
fc_y_pnh_002
/fc_y_pnh_003
are scored: No = 0; Yes = 2 -
fc_y_pnh_002__01
/fc_y_pnh_003__01
are scored with their original values (1 through 10)
-
Usage
vars_fc_y_pnh
compute_fc_y_pnh_sum(data, name = "fc_y_pnh_sum", max_na = 0, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_pnh is a character vector of all column names
used to compute summary score of fc_y_pnh
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Prosocial Behavior [Youth]: Mean"
Description
Computes the summary score fc_y_psb_mean
(Prosocial Behavior [Youth]: Mean)
-
Summarized variables:
-
fc_y_psb_001
-
fc_y_psb_002
-
fc_y_psb_003
-
-
Excluded values: none
-
Validation criterion: none of 3 items missing
Usage
vars_fc_y_psb
compute_fc_y_psb_mean(data, name = "fc_y_psb_mean", max_na = 0, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_psb is a character vector of all column names
used to compute summary score of fc_y_psb
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Resistance to Peer Influence [Youth]: Mean"
Description
Computes the summary score fc_y_rpi_mean
(Resistance to Peer Influence [Youth]: Mean)
-
Summarized variables:
-
fc_y_rpi_001
-
fc_y_rpi_002
-
fc_y_rpi_003
-
fc_y_rpi_004
-
fc_y_rpi_005
-
fc_y_rpi_006
-
fc_y_rpi_007
-
fc_y_rpi_008
-
fc_y_rpi_009
-
fc_y_rpi_010
-
-
Excluded values: none
-
Validation criterion: maximally 3 of 10 items missing
-
Note: The following variables are reverse coded before computing the summary score:
-
fc_y_rpi_002
-
fc_y_rpi_006
-
fc_y_rpi_010
-
Usage
vars_fc_y_rpi
compute_fc_y_rpi_mean(data, name = "fc_y_rpi_mean", max_na = 3, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 3). |
combine |
logical. If |
Format
vars_fc_y_rpi is a character vector of all column names
used to compute summary score of fc_y_rpi
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "School Risk & Protective Factors [Youth] (School disengagement): Mean"
Description
Computes the summary score fc_y_srpf__dis_mean
(School Risk & Protective Factors [Youth] (School disengagement): Mean)
-
Summarized variables:
-
fc_y_srpf__dis_001
-
fc_y_srpf__dis_002
-
-
Excluded values: none
-
Validation criterion: none of 2 items missing
Usage
vars_fc_y_srpf__dis
compute_fc_y_srpf__dis_mean(
data,
name = "fc_y_srpf__dis_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_srpf__dis is a character vector of all column names
used to compute summary score of fc_y_srpf__dis
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "School Risk & Protective Factors [Youth] (School environment): Mean"
Description
Computes the summary score fc_y_srpf__env_mean
(School Risk & Protective Factors [Youth] (School environment): Mean)
-
Summarized variables:
-
fc_y_srpf__env_001
-
fc_y_srpf__env_002
-
fc_y_srpf__env_003
-
fc_y_srpf__env_004
-
fc_y_srpf__env_005
-
fc_y_srpf__env_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_y_srpf__env
compute_fc_y_srpf__env_mean(
data,
name = "fc_y_srpf__env_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_srpf__env is a character vector of all column names
used to compute summary score of fc_y_srpf__env
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "School Risk & Protective Factors [Youth] (School involvement): Mean"
Description
Computes the summary score fc_y_srpf__involv_mean
(School Risk & Protective Factors [Youth] (School involvement): Mean)
-
Summarized variables:
-
fc_y_srpf__involv_001
-
fc_y_srpf__involv_002
-
fc_y_srpf__involv_003
-
fc_y_srpf__involv_004
-
-
Excluded values: none
-
Validation criterion: none of 4 items missing
Usage
vars_fc_y_srpf__involv
compute_fc_y_srpf__involv_mean(
data,
name = "fc_y_srpf__involv_mean",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
Format
vars_fc_y_srpf__involv is a character vector of all column names
used to compute summary score of fc_y_srpf__involv
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Youth] (Independence and self-reliance): Mean"
Description
Computes the summary score fc_y_vs__indselfrel_mean
(Values Scale [Youth] (Independence and
self-reliance): Mean)
-
Summarized variables:
-
fc_y_vs__indselfrel_001
-
fc_y_vs__indselfrel_002
-
fc_y_vs__indselfrel_003
-
fc_y_vs__indselfrel_004
-
fc_y_vs__indselfrel_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_vs__indselfrel
compute_fc_y_vs__indselfrel_mean(
data,
name = "fc_y_vs__indselfrel_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_vs__indselfrel is a character vector of all column names
used to compute summary score of fc_y_vs__indselfrel
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Youth] (Family obligation): Mean"
Description
Computes the summary score fc_y_vs__obl_mean
(Values Scale [Youth] (Family obligation): Mean)
-
Summarized variables:
-
fc_y_vs__obl_001
-
fc_y_vs__obl_002
-
fc_y_vs__obl_003
-
fc_y_vs__obl_004
-
fc_y_vs__obl_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_vs__obl
compute_fc_y_vs__obl_mean(
data,
name = "fc_y_vs__obl_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_vs__obl is a character vector of all column names
used to compute summary score of fc_y_vs__obl
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Youth] (Family as referent): Mean"
Description
Computes the summary score fc_y_vs__ref_mean
(Values Scale [Youth] (Family as referent): Mean)
-
Summarized variables:
-
fc_y_vs__ref_001
-
fc_y_vs__ref_002
-
fc_y_vs__ref_003
-
fc_y_vs__ref_004
-
fc_y_vs__ref_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_fc_y_vs__ref
compute_fc_y_vs__ref_mean(
data,
name = "fc_y_vs__ref_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_vs__ref is a character vector of all column names
used to compute summary score of fc_y_vs__ref
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Youth] (Religion): Mean"
Description
Computes the summary score fc_y_vs__relig_mean
(Values Scale [Youth] (Religion): Mean)
-
Summarized variables:
-
fc_y_vs__relig_001
-
fc_y_vs__relig_002
-
fc_y_vs__relig_003
-
fc_y_vs__relig_004
-
fc_y_vs__relig_005
-
fc_y_vs__relig_006
-
fc_y_vs__relig_007
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 7 items missing
Usage
vars_fc_y_vs__relig
compute_fc_y_vs__relig_mean(
data,
name = "fc_y_vs__relig_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_vs__relig is a character vector of all column names
used to compute summary score of fc_y_vs__relig
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Values Scale [Youth] (Family support): Mean"
Description
Computes the summary score fc_y_vs__supp_mean
(Values Scale [Youth] (Family support): Mean)
-
Summarized variables:
-
fc_y_vs__supp_001
-
fc_y_vs__supp_002
-
fc_y_vs__supp_003
-
fc_y_vs__supp_004
-
fc_y_vs__supp_005
-
fc_y_vs__supp_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_y_vs__supp
compute_fc_y_vs__supp_mean(
data,
name = "fc_y_vs__supp_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_vs__supp is a character vector of all column names
used to compute summary score of fc_y_vs__supp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Wills Problem Solving Scale [Youth]: Mean"
Description
Computes the summary score fc_y_wpss_mean
(Wills Problem Solving Scale [Youth]: Mean)
-
Summarized variables:
-
fc_y_wpss_001
-
fc_y_wpss_002
-
fc_y_wpss_003
-
fc_y_wpss_004
-
fc_y_wpss_005
-
fc_y_wpss_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_fc_y_wpss
compute_fc_y_wpss_mean(
data,
name = "fc_y_wpss_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
Format
vars_fc_y_wpss is a character vector of all column names
used to compute summary score of fc_y_wpss
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Adult Behavior Checklist [Parent]: Number missing"
Description
Computes the summary score mh_p_abcl_nm
Adult Behavior Checklist [Parent]: Number missing
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__rule_003
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__som_001
-
mh_p_abcl__othpr_001
-
mh_p_abcl__othpr_002
-
mh_p_abcl__othpr_003
-
mh_p_abcl__othpr_004
-
mh_p_abcl__othpr_005
-
mh_p_abcl__othpr_006
-
mh_p_abcl__othpr_007
-
mh_p_abcl__othpr_008
-
mh_p_abcl__othpr_009
-
mh_p_abcl__othpr_010
-
mh_p_abcl__othpr_011
-
mh_p_abcl__othpr_012
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl
compute_mh_p_abcl_nm(
data,
name = "mh_p_abcl_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl
is vector of all column names
used to compute summary score of mh_p_abcl
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl_nm(data) |>
select(
any_of(c("mh_p_abcl_nm", vars_mh_p_abcl))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Adaptive Functioning Scale - Friends): Number missing"
Description
Computes the summary score mh_p_abcl__afs__frnd_nm
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): Number missing
-
Summarized variables:
-
mh_p_abcl__frnd_001
-
mh_p_abcl__frnd_002
-
mh_p_abcl__frnd_003
-
mh_p_abcl__frnd_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__afs__frnd
compute_mh_p_abcl__afs__frnd_nm(
data,
name = "mh_p_abcl__afs__frnd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__afs__frnd
is vector of all column names
used to compute summary score of mh_p_abcl__afs__frnd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__afs__frnd_nm(data) |>
select(
any_of(c("mh_p_abcl__afs__frnd_nm", vars_mh_p_abcl__afs__frnd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] Sex Assignment"
Description
Computes the summary score mh_p_abcl__cg2_sex
Adult Behavior Checklist [Parent] Sex Assignment
-
Summarized variables:
-
mh_p_abcl__cg2_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__cg2
compute_mh_p_abcl__cg2_sex(data, name = "mh_p_abcl__cg2_sex", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
Format
vars_mh_p_abcl__cg2
is vector of all column names
used to compute summary score of mh_p_abcl__cg2
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__cg2_sex(data) |>
select(
any_of(c("mh_p_abcl__cg2_sex", vars_mh_p_abcl__cg2))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Critical items): Number missing"
Description
Computes the summary score mh_p_abcl__critic_nm
Adult Behavior Checklist [Parent] (Critical items): Number missing
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__tho_001
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_006
-
mh_p_abcl__rule_002
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__anxdep__dep_004
-
Usage
vars_mh_p_abcl__critic
compute_mh_p_abcl__critic_nm(
data,
name = "mh_p_abcl__critic_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__critic
is vector of all column names
used to compute summary score of mh_p_abcl__critic
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__critic_nm(data) |>
select(
any_of(c("mh_p_abcl__critic_nm", vars_mh_p_abcl__critic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__adhd_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
Number missing
-
Summarized variables:
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__rule__adhd_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__adhd
compute_mh_p_abcl__dsm__adhd_nm(
data,
name = "mh_p_abcl__dsm__adhd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__adhd
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__adhd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__adhd_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__adhd_nm", vars_mh_p_abcl__dsm__adhd))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial personality problems): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__antsoc_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Number missing
-
Summarized variables:
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__antsoc
compute_mh_p_abcl__dsm__antsoc_nm(
data,
name = "mh_p_abcl__dsm__antsoc_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__antsoc
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__antsoc
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__antsoc_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__antsoc_nm", vars_mh_p_abcl__dsm__antsoc))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety problems): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__anx_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): Number missing
-
Summarized variables:
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__anx
compute_mh_p_abcl__dsm__anx_nm(
data,
name = "mh_p_abcl__dsm__anx_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__anx
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__anx
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__anx_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__anx_nm", vars_mh_p_abcl__dsm__anx))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant personality problems): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__avoid_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Number missing
-
Summarized variables:
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__avoid
compute_mh_p_abcl__dsm__avoid_nm(
data,
name = "mh_p_abcl__dsm__avoid_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__avoid
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__avoid
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__avoid_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__avoid_nm", vars_mh_p_abcl__dsm__avoid))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__dep_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Number missing
-
Summarized variables:
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__dep
compute_mh_p_abcl__dsm__dep_nm(
data,
name = "mh_p_abcl__dsm__dep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__dep
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__dep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__dep_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__dep_nm", vars_mh_p_abcl__dsm__dep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_abcl__dsm__somat_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
-
Summarized variables:
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__dsm__somat
compute_mh_p_abcl__dsm__somat_nm(
data,
name = "mh_p_abcl__dsm__somat_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__dsm__somat
is vector of all column names
used to compute summary score of mh_p_abcl__dsm__somat
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__dsm__somat_nm(data) |>
select(
any_of(c("mh_p_abcl__dsm__somat_nm", vars_mh_p_abcl__dsm__somat))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Substance use): Number missing"
Description
Computes the summary score mh_p_abcl__su_nm
Adult Behavior Checklist [Parent] (Substance use): Number missing
-
Summarized variables:
-
mh_p_abcl__drg_001
-
mh_p_abcl__drunk_001
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__su
compute_mh_p_abcl__su_nm(
data,
name = "mh_p_abcl__su_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__su
is vector of all column names
used to compute summary score of mh_p_abcl__su
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__su_nm(data) |>
select(
any_of(c("mh_p_abcl__su_nm", vars_mh_p_abcl__su))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days drug use): Number missing"
Description
Computes the summary score mh_p_abcl__su__drg_nm
Adult Behavior Checklist [Parent] (Days drug use): Number missing
-
Summarized variables:
-
mh_p_abcl__drg_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__su__drg
compute_mh_p_abcl__su__drg_nm(
data,
name = "mh_p_abcl__su__drg_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__su__drg
is vector of all column names
used to compute summary score of mh_p_abcl__su__drg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__su__drg_nm(data) |>
select(
any_of(c("mh_p_abcl__su__drg_nm", vars_mh_p_abcl__su__drg))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Days Drunk): Number missing"
Description
Computes the summary score mh_p_abcl__su__drunk_nm
Adult Behavior Checklist [Parent] (Days Drunk): Number missing
-
Summarized variables:
-
mh_p_abcl__drunk_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__su__drunk
compute_mh_p_abcl__su__drunk_nm(
data,
name = "mh_p_abcl__su__drunk_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__su__drunk
is vector of all column names
used to compute summary score of mh_p_abcl__su__drunk
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__su__drunk_nm(data) |>
select(
any_of(c("mh_p_abcl__su__drunk_nm", vars_mh_p_abcl__su__drunk))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Tobacco per day): Number missing"
Description
Computes the summary score mh_p_abcl__su__nic_nm
Adult Behavior Checklist [Parent] (Tobacco per day): Number missing
-
Summarized variables:
-
mh_p_abcl__nic_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__su__nic
compute_mh_p_abcl__su__nic_nm(
data,
name = "mh_p_abcl__su__nic_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__su__nic
is vector of all column names
used to compute summary score of mh_p_abcl__su__nic
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__su__nic_nm(data) |>
select(
any_of(c("mh_p_abcl__su__nic_nm", vars_mh_p_abcl__su__nic))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): Number missing"
Description
Computes the summary score mh_p_abcl__synd__aggr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Number missing
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__aggr
compute_mh_p_abcl__synd__aggr_nm(
data,
name = "mh_p_abcl__synd__aggr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__aggr
is vector of all column names
used to compute summary score of mh_p_abcl__synd__aggr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__aggr_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__aggr_nm", vars_mh_p_abcl__synd__aggr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): Number missing"
Description
Computes the summary score mh_p_abcl__synd__anxdep_nm
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Number missing
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__anxdep
compute_mh_p_abcl__synd__anxdep_nm(
data,
name = "mh_p_abcl__synd__anxdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__anxdep
is vector of all column names
used to compute summary score of mh_p_abcl__synd__anxdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__anxdep_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__anxdep_nm", vars_mh_p_abcl__synd__anxdep))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Attention problems): Number missing"
Description
Computes the summary score mh_p_abcl__synd__attn_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Number missing
-
Summarized variables:
-
mh_p_abcl__attn_001
-
mh_p_abcl__attn_002
-
mh_p_abcl__attn_003
-
mh_p_abcl__attn_004
-
mh_p_abcl__attn_005
-
mh_p_abcl__attn_006
-
mh_p_abcl__attn__adhd_001
-
mh_p_abcl__attn__adhd_002
-
mh_p_abcl__attn__adhd_003
-
mh_p_abcl__attn__adhd_004
-
mh_p_abcl__attn__adhd_005
-
mh_p_abcl__attn__adhd_006
-
mh_p_abcl__attn__adhd_007
-
mh_p_abcl__attn__antsoc_001
-
mh_p_abcl__attn__dep_001
-
mh_p_abcl__attn__dep_002
-
mh_p_abcl__attn__dep_003
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__attn
compute_mh_p_abcl__synd__attn_nm(
data,
name = "mh_p_abcl__synd__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__attn
is vector of all column names
used to compute summary score of mh_p_abcl__synd__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__attn_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__attn_nm", vars_mh_p_abcl__synd__attn))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - External): Number missing"
Description
Computes the summary score mh_p_abcl__synd__ext_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - External): Number
missing
-
Summarized variables:
-
mh_p_abcl__aggr_001
-
mh_p_abcl__aggr_002
-
mh_p_abcl__aggr_003
-
mh_p_abcl__aggr_004
-
mh_p_abcl__aggr_005
-
mh_p_abcl__aggr_006
-
mh_p_abcl__aggr_007
-
mh_p_abcl__aggr__adhd_001
-
mh_p_abcl__aggr__antsoc_001
-
mh_p_abcl__aggr__antsoc_002
-
mh_p_abcl__aggr__antsoc_003
-
mh_p_abcl__aggr__antsoc_004
-
mh_p_abcl__aggr__antsoc_005
-
mh_p_abcl__aggr__antsoc_006
-
mh_p_abcl__aggr__antsoc_007
-
mh_p_abcl__aggr__antsoc_008
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__ext
compute_mh_p_abcl__synd__ext_nm(
data,
name = "mh_p_abcl__synd__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__ext
is vector of all column names
used to compute summary score of mh_p_abcl__synd__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__ext_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__ext_nm", vars_mh_p_abcl__synd__ext))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Internalizing): Number missing"
Description
Computes the summary score mh_p_abcl__synd__int_nm
Adult Behavior Checklist [Parent] (Internalizing): Number missing
-
Summarized variables:
-
mh_p_abcl__anxdep_001
-
mh_p_abcl__anxdep_002
-
mh_p_abcl__anxdep_003
-
mh_p_abcl__anxdep_004
-
mh_p_abcl__anxdep__anx_001
-
mh_p_abcl__anxdep__anx_002
-
mh_p_abcl__anxdep__anx_003
-
mh_p_abcl__anxdep__avoid_001
-
mh_p_abcl__anxdep__avoid_002
-
mh_p_abcl__anxdep__dep_001
-
mh_p_abcl__anxdep__dep_002
-
mh_p_abcl__anxdep__dep_003
-
mh_p_abcl__anxdep__dep_004
-
mh_p_abcl__anxdep__dep_005
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__int
compute_mh_p_abcl__synd__int_nm(
data,
name = "mh_p_abcl__synd__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__int
is vector of all column names
used to compute summary score of mh_p_abcl__synd__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__int_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__int_nm", vars_mh_p_abcl__synd__int))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Number missing"
Description
Computes the summary score mh_p_abcl__synd__intru_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Number
missing
-
Summarized variables:
-
mh_p_abcl__intru_001
-
mh_p_abcl__intru_002
-
mh_p_abcl__intru_003
-
mh_p_abcl__intru_004
-
mh_p_abcl__intru_005
-
mh_p_abcl__intru_006
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__intru
compute_mh_p_abcl__synd__intru_nm(
data,
name = "mh_p_abcl__synd__intru_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__intru
is vector of all column names
used to compute summary score of mh_p_abcl__synd__intru
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__intru_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__intru_nm", vars_mh_p_abcl__synd__intru))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems): Number missing"
Description
Computes the summary score mh_p_abcl__synd__othpr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Number missing
-
Summarized variables:
-
mh_p_abcl__othpr_001
-
mh_p_abcl__othpr_002
-
mh_p_abcl__othpr_003
-
mh_p_abcl__othpr_004
-
mh_p_abcl__othpr_005
-
mh_p_abcl__othpr_006
-
mh_p_abcl__othpr_007
-
mh_p_abcl__othpr_008
-
mh_p_abcl__othpr_009
-
mh_p_abcl__othpr_010
-
mh_p_abcl__othpr_011
-
mh_p_abcl__othpr_012
-
mh_p_abcl__othpr__adhd_001
-
mh_p_abcl__othpr__adhd_002
-
mh_p_abcl__othpr__adhd_003
-
mh_p_abcl__othpr__adhd_004
-
mh_p_abcl__othpr__antsoc_001
-
mh_p_abcl__othpr__antsoc_002
-
mh_p_abcl__othpr__anx_001
-
mh_p_abcl__othpr__anx_002
-
mh_p_abcl__othpr__anx_003
-
mh_p_abcl__othpr__avoid_001
-
mh_p_abcl__othpr__dep_001
-
mh_p_abcl__othpr__dep_002
-
mh_p_abcl__othpr__dep_003
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__othpr
compute_mh_p_abcl__synd__othpr_nm(
data,
name = "mh_p_abcl__synd__othpr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__othpr
is vector of all column names
used to compute summary score of mh_p_abcl__synd__othpr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__othpr_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__othpr_nm", vars_mh_p_abcl__synd__othpr))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): Number missing"
Description
Computes the summary score mh_p_abcl__synd__rule_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Number missing
-
Summarized variables:
-
mh_p_abcl__rule_001
-
mh_p_abcl__rule_002
-
mh_p_abcl__rule_003
-
mh_p_abcl__rule__adhd_001
-
mh_p_abcl__rule__antsoc_001
-
mh_p_abcl__rule__antsoc_002
-
mh_p_abcl__rule__antsoc_003
-
mh_p_abcl__rule__antsoc_004
-
mh_p_abcl__rule__antsoc_005
-
mh_p_abcl__rule__antsoc_006
-
mh_p_abcl__rule__antsoc_007
-
mh_p_abcl__rule__antsoc_008
-
mh_p_abcl__rule__antsoc_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__rule
compute_mh_p_abcl__synd__rule_nm(
data,
name = "mh_p_abcl__synd__rule_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__rule
is vector of all column names
used to compute summary score of mh_p_abcl__synd__rule
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__rule_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__rule_nm", vars_mh_p_abcl__synd__rule))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_abcl__synd__som_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Number missing
-
Summarized variables:
-
mh_p_abcl__som_001
-
mh_p_abcl__som__dep_001
-
mh_p_abcl__som__somat_001
-
mh_p_abcl__som__somat_002
-
mh_p_abcl__som__somat_003
-
mh_p_abcl__som__somat_004
-
mh_p_abcl__som__somat_005
-
mh_p_abcl__som__somat_006
-
mh_p_abcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__som
compute_mh_p_abcl__synd__som_nm(
data,
name = "mh_p_abcl__synd__som_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__som
is vector of all column names
used to compute summary score of mh_p_abcl__synd__som
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__som_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__som_nm", vars_mh_p_abcl__synd__som))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems): Number missing"
Description
Computes the summary score mh_p_abcl__synd__tho_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Number missing
-
Summarized variables:
-
mh_p_abcl__tho_001
-
mh_p_abcl__tho_002
-
mh_p_abcl__tho_003
-
mh_p_abcl__tho_004
-
mh_p_abcl__tho_005
-
mh_p_abcl__tho_006
-
mh_p_abcl__tho_007
-
mh_p_abcl__tho__dep_001
-
mh_p_abcl__tho__dep_002
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__tho
compute_mh_p_abcl__synd__tho_nm(
data,
name = "mh_p_abcl__synd__tho_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__tho
is vector of all column names
used to compute summary score of mh_p_abcl__synd__tho
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__tho_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__tho_nm", vars_mh_p_abcl__synd__tho))
)
## End(Not run)
Compute "Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Number missing"
Description
Computes the summary score mh_p_abcl__synd__wthdr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Number
missing
-
Summarized variables:
-
mh_p_abcl__wthdr_001
-
mh_p_abcl__wthdr_002
-
mh_p_abcl__wthdr_003
-
mh_p_abcl__wthdr_004
-
mh_p_abcl__wthdr__avoid_001
-
mh_p_abcl__wthdr__avoid_002
-
mh_p_abcl__wthdr__avoid_003
-
mh_p_abcl__wthdr__avoid_004
-
mh_p_abcl__wthdr__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_abcl__synd__wthdr
compute_mh_p_abcl__synd__wthdr_nm(
data,
name = "mh_p_abcl__synd__wthdr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_abcl__synd__wthdr
is vector of all column names
used to compute summary score of mh_p_abcl__synd__wthdr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_abcl__synd__wthdr_nm(data) |>
select(
any_of(c("mh_p_abcl__synd__wthdr_nm", vars_mh_p_abcl__synd__wthdr))
)
## End(Not run)
Compute "Adult Self Report [Parent]: Number missing"
Description
Computes the summary score mh_p_asr_nm
Adult Self Report [Parent]: Number missing
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__rule_001
-
mh_p_asr__rule_003
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho__dep_001
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__wthdr__dep_001
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__attn_001
-
mh_p_asr__attn_002
-
mh_p_asr__attn_003
-
mh_p_asr__attn_004
-
mh_p_asr__attn_005
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
mh_p_asr__rule_002
-
mh_p_asr__rule_004
-
mh_p_asr__som_001
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__othpr_001
-
mh_p_asr__othpr_002
-
mh_p_asr__othpr_003
-
mh_p_asr__othpr_004
-
mh_p_asr__othpr_005
-
mh_p_asr__othpr_006
-
mh_p_asr__othpr_007
-
mh_p_asr__othpr_008
-
mh_p_asr__othpr_009
-
mh_p_asr__othpr_010
-
mh_p_asr__othpr_011
-
mh_p_asr__tho_003
-
mh_p_asr__tho_004
-
mh_p_asr__tho_008
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr
compute_mh_p_asr_nm(
data,
name = "mh_p_asr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr
is vector of all column names
used to compute summary score of mh_p_asr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr_nm(data) |>
select(
any_of(c("mh_p_asr_nm", vars_mh_p_asr))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Adaptive Functioning Scale - Personal strength): Number missing"
Description
Computes the summary score mh_p_asr__afs__strng_nm
Adult Self Report [Parent] (Adaptive Functioning Scale - Personal
strength): Number missing
-
Summarized variables:
-
mh_p_asr__strng_001
-
mh_p_asr__strng_002
-
mh_p_asr__strng_003
-
mh_p_asr__strng_004
-
mh_p_asr__strng_005
-
mh_p_asr__strng_006
-
mh_p_asr__strng_007
-
mh_p_asr__strng_008
-
mh_p_asr__strng_009
-
mh_p_asr__strng_010
-
mh_p_asr__strng_011
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__afs__strng
compute_mh_p_asr__afs__strng_nm(
data,
name = "mh_p_asr__afs__strng_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__afs__strng
is vector of all column names
used to compute summary score of mh_p_asr__afs__strng
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__afs__strng_nm(data) |>
select(
any_of(c("mh_p_asr__afs__strng_nm", vars_mh_p_asr__afs__strng))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Critical Items): Number missing"
Description
Computes the summary score mh_p_asr__critic_nm
Adult Self Report [Parent] (Critical Items): Number missing
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__rule_001
-
mh_p_asr__rule_003
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__critic
compute_mh_p_asr__critic_nm(
data,
name = "mh_p_asr__critic_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__critic
is vector of all column names
used to compute summary score of mh_p_asr__critic
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__critic_nm(data) |>
select(
any_of(c("mh_p_asr__critic_nm", vars_mh_p_asr__critic))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Number missing"
Description
Computes the summary score mh_p_asr__dsm__adhd_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Number
missing
-
Summarized variables:
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__adhd
compute_mh_p_asr__dsm__adhd_nm(
data,
name = "mh_p_asr__dsm__adhd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__adhd
is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__adhd_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd_nm", vars_mh_p_asr__dsm__adhd))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Hyperactivity-Impulsivity): Number missing"
Description
Computes the summary score mh_p_asr__dsm__adhd__hypimp_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD
Hyperactivity-Impulsivity): Number missing
-
Summarized variables:
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__tho__hypimp_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__adhd__hypimp
compute_mh_p_asr__dsm__adhd__hypimp_nm(
data,
name = "mh_p_asr__dsm__adhd__hypimp_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__adhd__hypimp
is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd__hypimp
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__adhd__hypimp_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd__hypimp_nm", vars_mh_p_asr__dsm__adhd__hypimp))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention): Number missing"
Description
Computes the summary score mh_p_asr__dsm__adhd__inatt_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention):
Number missing
-
Summarized variables:
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__adhd__inatt
compute_mh_p_asr__dsm__adhd__inatt_nm(
data,
name = "mh_p_asr__dsm__adhd__inatt_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__adhd__inatt
is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd__inatt
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__adhd__inatt_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__adhd__inatt_nm", vars_mh_p_asr__dsm__adhd__inatt))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial personality problems): Number missing"
Description
Computes the summary score mh_p_asr__dsm__antsoc_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Number missing
-
Summarized variables:
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__antsoc
compute_mh_p_asr__dsm__antsoc_nm(
data,
name = "mh_p_asr__dsm__antsoc_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__antsoc
is vector of all column names
used to compute summary score of mh_p_asr__dsm__antsoc
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__antsoc_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__antsoc_nm", vars_mh_p_asr__dsm__antsoc))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems): Number missing"
Description
Computes the summary score mh_p_asr__dsm__anx_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems):
Number missing
-
Summarized variables:
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__anx
compute_mh_p_asr__dsm__anx_nm(
data,
name = "mh_p_asr__dsm__anx_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__anx
is vector of all column names
used to compute summary score of mh_p_asr__dsm__anx
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__anx_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__anx_nm", vars_mh_p_asr__dsm__anx))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant personality problems): Number missing"
Description
Computes the summary score mh_p_asr__dsm__avoid_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Number missing
-
Summarized variables:
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__avoid
compute_mh_p_asr__dsm__avoid_nm(
data,
name = "mh_p_asr__dsm__avoid_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__avoid
is vector of all column names
used to compute summary score of mh_p_asr__dsm__avoid
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__avoid_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__avoid_nm", vars_mh_p_asr__dsm__avoid))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive problems): Number missing"
Description
Computes the summary score mh_p_asr__dsm__dep_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive
problems): Number missing
-
Summarized variables:
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__tho__dep_001
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__dep
compute_mh_p_asr__dsm__dep_nm(
data,
name = "mh_p_asr__dsm__dep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__dep
is vector of all column names
used to compute summary score of mh_p_asr__dsm__dep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__dep_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__dep_nm", vars_mh_p_asr__dsm__dep))
)
## End(Not run)
Compute "Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_asr__dsm__somat_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
-
Summarized variables:
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__dsm__somat
compute_mh_p_asr__dsm__somat_nm(
data,
name = "mh_p_asr__dsm__somat_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__dsm__somat
is vector of all column names
used to compute summary score of mh_p_asr__dsm__somat
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__dsm__somat_nm(data) |>
select(
any_of(c("mh_p_asr__dsm__somat_nm", vars_mh_p_asr__dsm__somat))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior): Number missing"
Description
Computes the summary score mh_p_asr__synd__aggr_nm
Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior):
Number missing
-
Summarized variables:
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__aggr
compute_mh_p_asr__synd__aggr_nm(
data,
name = "mh_p_asr__synd__aggr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__aggr
is vector of all column names
used to compute summary score of mh_p_asr__synd__aggr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__aggr_nm(data) |>
select(
any_of(c("mh_p_asr__synd__aggr_nm", vars_mh_p_asr__synd__aggr))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed): Number missing"
Description
Computes the summary score mh_p_asr__synd__anxdep_nm
Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed):
Number missing
-
Summarized variables:
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__anxdep
compute_mh_p_asr__synd__anxdep_nm(
data,
name = "mh_p_asr__synd__anxdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__anxdep
is vector of all column names
used to compute summary score of mh_p_asr__synd__anxdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__anxdep_nm(data) |>
select(
any_of(c("mh_p_asr__synd__anxdep_nm", vars_mh_p_asr__synd__anxdep))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Attention problems): Number missing"
Description
Computes the summary score mh_p_asr__synd__attn_nm
Adult Self Report [Parent] (Syndrome Scale - Attention problems):
Number missing
-
Summarized variables:
-
mh_p_asr__attn_001
-
mh_p_asr__attn_002
-
mh_p_asr__attn_003
-
mh_p_asr__attn_004
-
mh_p_asr__attn_005
-
mh_p_asr__attn__inatt_001
-
mh_p_asr__attn__inatt_002
-
mh_p_asr__attn__inatt_003
-
mh_p_asr__attn__inatt_004
-
mh_p_asr__attn__inatt_005
-
mh_p_asr__attn__inatt_006
-
mh_p_asr__attn__inatt_007
-
mh_p_asr__attn__antsoc_001
-
mh_p_asr__attn__dep_001
-
mh_p_asr__attn__dep_002
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__attn
compute_mh_p_asr__synd__attn_nm(
data,
name = "mh_p_asr__synd__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__attn
is vector of all column names
used to compute summary score of mh_p_asr__synd__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__attn_nm(data) |>
select(
any_of(c("mh_p_asr__synd__attn_nm", vars_mh_p_asr__synd__attn))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Externalizing): Number missing"
Description
Computes the summary score mh_p_asr__synd__ext_nm
Adult Self Report [Parent] (Syndrome Scale - Externalizing): Number
missing
-
Summarized variables:
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
mh_p_asr__rule_001
-
mh_p_asr__rule_002
-
mh_p_asr__rule_003
-
mh_p_asr__rule_004
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
mh_p_asr__aggr_001
-
mh_p_asr__aggr_002
-
mh_p_asr__aggr_003
-
mh_p_asr__aggr_004
-
mh_p_asr__aggr_005
-
mh_p_asr__aggr_006
-
mh_p_asr__aggr__hypimp_001
-
mh_p_asr__aggr__antsoc_001
-
mh_p_asr__aggr__antsoc_002
-
mh_p_asr__aggr__antsoc_003
-
mh_p_asr__aggr__antsoc_004
-
mh_p_asr__aggr__antsoc_005
-
mh_p_asr__aggr__antsoc_006
-
mh_p_asr__aggr__antsoc_007
-
mh_p_asr__aggr__antsoc_008
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__ext
compute_mh_p_asr__synd__ext_nm(
data,
name = "mh_p_asr__synd__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__ext
is vector of all column names
used to compute summary score of mh_p_asr__synd__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__ext_nm(data) |>
select(
any_of(c("mh_p_asr__synd__ext_nm", vars_mh_p_asr__synd__ext))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Internalizing): Number missing"
Description
Computes the summary score mh_p_asr__synd__int_nm
Adult Self Report [Parent] (Syndrome Scale - Internalizing): Number
missing
-
Summarized variables:
-
mh_p_asr__anxdep_001
-
mh_p_asr__anxdep_002
-
mh_p_asr__anxdep_003
-
mh_p_asr__anxdep_004
-
mh_p_asr__anxdep_005
-
mh_p_asr__anxdep_006
-
mh_p_asr__anxdep__anx_001
-
mh_p_asr__anxdep__anx_002
-
mh_p_asr__anxdep__anx_003
-
mh_p_asr__anxdep__anx_004
-
mh_p_asr__anxdep__avoid_001
-
mh_p_asr__anxdep__avoid_002
-
mh_p_asr__anxdep__dep_001
-
mh_p_asr__anxdep__dep_002
-
mh_p_asr__anxdep__dep_003
-
mh_p_asr__anxdep__dep_004
-
mh_p_asr__anxdep__dep_005
-
mh_p_asr__anxdep__dep_006
-
mh_p_asr__som_001
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__int
compute_mh_p_asr__synd__int_nm(
data,
name = "mh_p_asr__synd__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__int
is vector of all column names
used to compute summary score of mh_p_asr__synd__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__int_nm(data) |>
select(
any_of(c("mh_p_asr__synd__int_nm", vars_mh_p_asr__synd__int))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Intrusive): Number missing"
Description
Computes the summary score mh_p_asr__synd__intru_nm
Adult Self Report [Parent] (Syndrome Scale - Intrusive): Number
missing
-
Summarized variables:
-
mh_p_asr__intru_001
-
mh_p_asr__intru_002
-
mh_p_asr__intru_003
-
mh_p_asr__intru_004
-
mh_p_asr__intru_005
-
mh_p_asr__intru_006
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__intru
compute_mh_p_asr__synd__intru_nm(
data,
name = "mh_p_asr__synd__intru_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__intru
is vector of all column names
used to compute summary score of mh_p_asr__synd__intru
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__intru_nm(data) |>
select(
any_of(c("mh_p_asr__synd__intru_nm", vars_mh_p_asr__synd__intru))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Other problems): Number missing"
Description
Computes the summary score mh_p_asr__synd__othpr_nm
Adult Self Report [Parent] (Syndrome Scale - Other problems): Number
missing
-
Summarized variables:
-
mh_p_asr__othpr_001
-
mh_p_asr__othpr_002
-
mh_p_asr__othpr_003
-
mh_p_asr__othpr_004
-
mh_p_asr__othpr_005
-
mh_p_asr__othpr_006
-
mh_p_asr__othpr_007
-
mh_p_asr__othpr_008
-
mh_p_asr__othpr_009
-
mh_p_asr__othpr_010
-
mh_p_asr__othpr_011
-
mh_p_asr__othpr__hypimp_001
-
mh_p_asr__othpr__hypimp_002
-
mh_p_asr__othpr__hypimp_003
-
mh_p_asr__othpr__antsoc_001
-
mh_p_asr__othpr__antsoc_002
-
mh_p_asr__othpr__anx_001
-
mh_p_asr__othpr__anx_002
-
mh_p_asr__othpr__avoid_001
-
mh_p_asr__othpr__dep_001
-
mh_p_asr__othpr__dep_002
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__othpr
compute_mh_p_asr__synd__othpr_nm(
data,
name = "mh_p_asr__synd__othpr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__othpr
is vector of all column names
used to compute summary score of mh_p_asr__synd__othpr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__othpr_nm(data) |>
select(
any_of(c("mh_p_asr__synd__othpr_nm", vars_mh_p_asr__synd__othpr))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior): Number missing"
Description
Computes the summary score mh_p_asr__synd__rule_nm
Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior):
Number missing
-
Summarized variables:
-
mh_p_asr__rule_001
-
mh_p_asr__rule_002
-
mh_p_asr__rule_003
-
mh_p_asr__rule_004
-
mh_p_asr__rule__hypimp_001
-
mh_p_asr__rule__antsoc_001
-
mh_p_asr__rule__antsoc_002
-
mh_p_asr__rule__antsoc_003
-
mh_p_asr__rule__antsoc_004
-
mh_p_asr__rule__antsoc_005
-
mh_p_asr__rule__antsoc_006
-
mh_p_asr__rule__antsoc_007
-
mh_p_asr__rule__antsoc_008
-
mh_p_asr__rule__antsoc_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__rule
compute_mh_p_asr__synd__rule_nm(
data,
name = "mh_p_asr__synd__rule_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__rule
is vector of all column names
used to compute summary score of mh_p_asr__synd__rule
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__rule_nm(data) |>
select(
any_of(c("mh_p_asr__synd__rule_nm", vars_mh_p_asr__synd__rule))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_asr__synd__som_nm
Adult Self Report [Parent] (Syndrome Scale - Somatic complaints):
Number missing
-
Summarized variables:
-
mh_p_asr__som_001
-
mh_p_asr__som__dep_001
-
mh_p_asr__som__dep_002
-
mh_p_asr__som__somat_001
-
mh_p_asr__som__somat_002
-
mh_p_asr__som__somat_003
-
mh_p_asr__som__somat_004
-
mh_p_asr__som__somat_005
-
mh_p_asr__som__somat_006
-
mh_p_asr__som__somat_007
-
mh_p_asr__som__somat_008
-
mh_p_asr__som__somat_009
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__som
compute_mh_p_asr__synd__som_nm(
data,
name = "mh_p_asr__synd__som_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__som
is vector of all column names
used to compute summary score of mh_p_asr__synd__som
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__som_nm(data) |>
select(
any_of(c("mh_p_asr__synd__som_nm", vars_mh_p_asr__synd__som))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Thought problems): Number missing"
Description
Computes the summary score mh_p_asr__synd__tho_nm
Adult Self Report [Parent] (Syndrome Scale - Thought problems): Number
missing
-
Summarized variables:
-
mh_p_asr__tho_001
-
mh_p_asr__tho_002
-
mh_p_asr__tho_003
-
mh_p_asr__tho_004
-
mh_p_asr__tho_005
-
mh_p_asr__tho_006
-
mh_p_asr__tho_007
-
mh_p_asr__tho_008
-
mh_p_asr__tho__hypimp_001
-
mh_p_asr__tho__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__tho
compute_mh_p_asr__synd__tho_nm(
data,
name = "mh_p_asr__synd__tho_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__tho
is vector of all column names
used to compute summary score of mh_p_asr__synd__tho
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__tho_nm(data) |>
select(
any_of(c("mh_p_asr__synd__tho_nm", vars_mh_p_asr__synd__tho))
)
## End(Not run)
Compute "Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Number missing"
Description
Computes the summary score mh_p_asr__synd__wthdr_nm
Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Number
missing
-
Summarized variables:
-
mh_p_asr__wthdr_001
-
mh_p_asr__wthdr_002
-
mh_p_asr__wthdr_003
-
mh_p_asr__wthdr_004
-
mh_p_asr__wthdr__avoid_001
-
mh_p_asr__wthdr__avoid_002
-
mh_p_asr__wthdr__avoid_003
-
mh_p_asr__wthdr__avoid_004
-
mh_p_asr__wthdr__dep_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_asr__synd__wthdr
compute_mh_p_asr__synd__wthdr_nm(
data,
name = "mh_p_asr__synd__wthdr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_asr__synd__wthdr
is vector of all column names
used to compute summary score of mh_p_asr__synd__wthdr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_asr__synd__wthdr_nm(data) |>
select(
any_of(c("mh_p_asr__synd__wthdr_nm", vars_mh_p_asr__synd__wthdr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale): Number missing"
Description
Computes the summary score mh_p_cbcl_nm
Child Behavior Checklist [Parent] (Syndrome Scale): Number missing
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__othpr_001
-
mh_p_cbcl__othpr_002
-
mh_p_cbcl__othpr_009
-
mh_p_cbcl__othpr_010
-
mh_p_cbcl__othpr_011
-
mh_p_cbcl__othpr_012
-
mh_p_cbcl__othpr_003
-
mh_p_cbcl__othpr_004
-
mh_p_cbcl__othpr_005
-
mh_p_cbcl__othpr_006
-
mh_p_cbcl__othpr_007
-
mh_p_cbcl__othpr_008
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl
compute_mh_p_cbcl_nm(
data,
name = "mh_p_cbcl_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl
is vector of all column names
used to compute summary score of mh_p_cbcl
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl_nm(data) |>
select(
any_of(c("mh_p_cbcl_nm", vars_mh_p_cbcl))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__adhd_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
Number missing
-
Summarized variables:
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__othpr__adhd_001
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__adhd
compute_mh_p_cbcl__dsm__adhd_nm(
data,
name = "mh_p_cbcl__dsm__adhd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__adhd
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__adhd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__adhd_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__adhd_nm", vars_mh_p_cbcl__dsm__adhd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__anx_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
Number missing
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__anx_006
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__anx
compute_mh_p_cbcl__dsm__anx_nm(
data,
name = "mh_p_cbcl__dsm__anx_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__anx
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__anx
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__anx_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__anx_nm", vars_mh_p_cbcl__dsm__anx))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct problems): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__cond_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): Number missing
-
Summarized variables:
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__cond
compute_mh_p_cbcl__dsm__cond_nm(
data,
name = "mh_p_cbcl__dsm__cond_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__cond
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__cond
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__cond_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__cond_nm", vars_mh_p_cbcl__dsm__cond))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive problems): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__dep_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Number missing
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__dep
compute_mh_p_cbcl__dsm__dep_nm(
data,
name = "mh_p_cbcl__dsm__dep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__dep
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__dep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__dep_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__dep_nm", vars_mh_p_cbcl__dsm__dep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional Defiant problems): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__opp_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): Number missing
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr__opp_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__opp
compute_mh_p_cbcl__dsm__opp_nm(
data,
name = "mh_p_cbcl__dsm__opp_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__opp
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__opp
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__opp_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__opp_nm", vars_mh_p_cbcl__dsm__opp))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_cbcl__dsm__somat_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
-
Summarized variables:
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__dsm__somat
compute_mh_p_cbcl__dsm__somat_nm(
data,
name = "mh_p_cbcl__dsm__somat_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__dsm__somat
is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__somat
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__dsm__somat_nm(data) |>
select(
any_of(c("mh_p_cbcl__dsm__somat_nm", vars_mh_p_cbcl__dsm__somat))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems): Number missing"
Description
Computes the summary score mh_p_cbcl__ocd_nm
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems):
Number missing
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__ocd
compute_mh_p_cbcl__ocd_nm(
data,
name = "mh_p_cbcl__ocd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__ocd
is vector of all column names
used to compute summary score of mh_p_cbcl__ocd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__ocd_nm(data) |>
select(
any_of(c("mh_p_cbcl__ocd_nm", vars_mh_p_cbcl__ocd))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Number missing"
Description
Computes the summary score mh_p_cbcl__sct_nm
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Number
missing
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__sct
compute_mh_p_cbcl__sct_nm(
data,
name = "mh_p_cbcl__sct_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__sct
is vector of all column names
used to compute summary score of mh_p_cbcl__sct
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__sct_nm(data) |>
select(
any_of(c("mh_p_cbcl__sct_nm", vars_mh_p_cbcl__sct))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Stress): Number missing"
Description
Computes the summary score mh_p_cbcl__strs_nm
Child Behavior Checklist [Parent] (Stress): Number missing
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__aggr_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__strs
compute_mh_p_cbcl__strs_nm(
data,
name = "mh_p_cbcl__strs_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__strs
is vector of all column names
used to compute summary score of mh_p_cbcl__strs
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__strs_nm(data) |>
select(
any_of(c("mh_p_cbcl__strs_nm", vars_mh_p_cbcl__strs))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive behavior): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__aggr_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Number missing
-
Summarized variables:
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__aggr
compute_mh_p_cbcl__synd__aggr_nm(
data,
name = "mh_p_cbcl__synd__aggr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__aggr
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__aggr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__aggr_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__aggr_nm", vars_mh_p_cbcl__synd__aggr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Anxious/Depressed): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__anxdep_nm
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Number missing
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__anxdep
compute_mh_p_cbcl__synd__anxdep_nm(
data,
name = "mh_p_cbcl__synd__anxdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__anxdep
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__anxdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__anxdep_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__anxdep_nm", vars_mh_p_cbcl__synd__anxdep))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Attention problems): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__attn_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Number missing
-
Summarized variables:
-
mh_p_cbcl__attn_001
-
mh_p_cbcl__attn__adhd_001
-
mh_p_cbcl__attn__adhd_002
-
mh_p_cbcl__attn__adhd_003
-
mh_p_cbcl__attn_002
-
mh_p_cbcl__attn_003
-
mh_p_cbcl__attn__adhd_004
-
mh_p_cbcl__attn_004
-
mh_p_cbcl__attn__adhd_005
-
mh_p_cbcl__attn_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__attn
compute_mh_p_cbcl__synd__attn_nm(
data,
name = "mh_p_cbcl__synd__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__attn
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__attn_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__attn_nm", vars_mh_p_cbcl__synd__attn))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__ext_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
Number missing
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
mh_p_cbcl__aggr__opp_001
-
mh_p_cbcl__aggr__adhd_001
-
mh_p_cbcl__aggr__cond_001
-
mh_p_cbcl__aggr_001
-
mh_p_cbcl__aggr_002
-
mh_p_cbcl__aggr__cond_002
-
mh_p_cbcl__aggr__opp_002
-
mh_p_cbcl__aggr__opp_003
-
mh_p_cbcl__aggr__cond_003
-
mh_p_cbcl__aggr__cond_004
-
mh_p_cbcl__aggr_003
-
mh_p_cbcl__aggr__opp_004
-
mh_p_cbcl__aggr_004
-
mh_p_cbcl__aggr_005
-
mh_p_cbcl__aggr_006
-
mh_p_cbcl__aggr_007
-
mh_p_cbcl__aggr__opp_005
-
mh_p_cbcl__aggr__cond_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__ext
compute_mh_p_cbcl__synd__ext_nm(
data,
name = "mh_p_cbcl__synd__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__ext
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__ext_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__ext_nm", vars_mh_p_cbcl__synd__ext))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__int_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Number missing
-
Summarized variables:
-
mh_p_cbcl__anxdep__anx_007
-
mh_p_cbcl__anxdep__dep_001
-
mh_p_cbcl__anxdep__anx_001
-
mh_p_cbcl__anxdep__anx_002
-
mh_p_cbcl__anxdep__anx_003
-
mh_p_cbcl__anxdep_001
-
mh_p_cbcl__anxdep_002
-
mh_p_cbcl__anxdep__dep_002
-
mh_p_cbcl__anxdep__anx_004
-
mh_p_cbcl__anxdep__anx_005
-
mh_p_cbcl__anxdep__dep_003
-
mh_p_cbcl__anxdep__anx_006
-
mh_p_cbcl__anxdep__dep_004
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__int
compute_mh_p_cbcl__synd__int_nm(
data,
name = "mh_p_cbcl__synd__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__int
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__int_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__int_nm", vars_mh_p_cbcl__synd__int))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Other problems): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__othpr_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Number missing
-
Summarized variables:
-
mh_p_cbcl__othpr_001
-
mh_p_cbcl__othpr_002
-
mh_p_cbcl__othpr_009
-
mh_p_cbcl__othpr_010
-
mh_p_cbcl__othpr_011
-
mh_p_cbcl__othpr_012
-
mh_p_cbcl__othpr__cond_001
-
mh_p_cbcl__othpr__dep_001
-
mh_p_cbcl__othpr_003
-
mh_p_cbcl__othpr_004
-
mh_p_cbcl__othpr_005
-
mh_p_cbcl__othpr_006
-
mh_p_cbcl__othpr_007
-
mh_p_cbcl__othpr__dep_002
-
mh_p_cbcl__othpr__adhd_001
-
mh_p_cbcl__othpr_008
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__othpr
compute_mh_p_cbcl__synd__othpr_nm(
data,
name = "mh_p_cbcl__synd__othpr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__othpr
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__othpr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__othpr_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__othpr_nm", vars_mh_p_cbcl__synd__othpr))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking behavior): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__rule_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Number missing
-
Summarized variables:
-
mh_p_cbcl__rule_001
-
mh_p_cbcl__rule__cond_010
-
mh_p_cbcl__rule_006
-
mh_p_cbcl__rule__cond_011
-
mh_p_cbcl__rule__cond_001
-
mh_p_cbcl__rule__cond_002
-
mh_p_cbcl__rule__cond_003
-
mh_p_cbcl__rule__cond_004
-
mh_p_cbcl__rule_002
-
mh_p_cbcl__rule__cond_005
-
mh_p_cbcl__rule__cond_006
-
mh_p_cbcl__rule_003
-
mh_p_cbcl__rule__cond_007
-
mh_p_cbcl__rule__cond_008
-
mh_p_cbcl__rule__cond_009
-
mh_p_cbcl__rule_004
-
mh_p_cbcl__rule_005
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__rule
compute_mh_p_cbcl__synd__rule_nm(
data,
name = "mh_p_cbcl__synd__rule_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__rule
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__rule
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__rule_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__rule_nm", vars_mh_p_cbcl__synd__rule))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale -Social): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__soc_nm
Child Behavior Checklist [Parent] (Syndrome Scale -Social): Number
missing
-
Summarized variables:
-
mh_p_cbcl__soc__anx_001
-
mh_p_cbcl__soc_001
-
mh_p_cbcl__soc_002
-
mh_p_cbcl__soc_003
-
mh_p_cbcl__soc_004
-
mh_p_cbcl__soc_005
-
mh_p_cbcl__soc_006
-
mh_p_cbcl__soc_007
-
mh_p_cbcl__soc_008
-
mh_p_cbcl__soc_009
-
mh_p_cbcl__soc_010
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__soc
compute_mh_p_cbcl__synd__soc_nm(
data,
name = "mh_p_cbcl__synd__soc_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__soc
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__soc
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__soc_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__soc_nm", vars_mh_p_cbcl__synd__soc))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__som_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Number missing
-
Summarized variables:
-
mh_p_cbcl__som__anx_001
-
mh_p_cbcl__som_001
-
mh_p_cbcl__som_002
-
mh_p_cbcl__som__dep_001
-
mh_p_cbcl__som__somat_001
-
mh_p_cbcl__som__somat_002
-
mh_p_cbcl__som__somat_003
-
mh_p_cbcl__som__somat_004
-
mh_p_cbcl__som__somat_005
-
mh_p_cbcl__som__somat_006
-
mh_p_cbcl__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__som
compute_mh_p_cbcl__synd__som_nm(
data,
name = "mh_p_cbcl__synd__som_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__som
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__som
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__som_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__som_nm", vars_mh_p_cbcl__synd__som))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__tho_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Number missing
-
Summarized variables:
-
mh_p_cbcl__tho_001
-
mh_p_cbcl__tho__dep_003
-
mh_p_cbcl__tho__dep_001
-
mh_p_cbcl__tho_002
-
mh_p_cbcl__tho_003
-
mh_p_cbcl__tho_004
-
mh_p_cbcl__tho_005
-
mh_p_cbcl__tho_006
-
mh_p_cbcl__tho_007
-
mh_p_cbcl__tho_008
-
mh_p_cbcl__tho__dep_002
-
mh_p_cbcl__tho_009
-
mh_p_cbcl__tho_010
-
mh_p_cbcl__tho_011
-
mh_p_cbcl__tho_012
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__tho
compute_mh_p_cbcl__synd__tho_nm(
data,
name = "mh_p_cbcl__synd__tho_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__tho
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__tho
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__tho_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__tho_nm", vars_mh_p_cbcl__synd__tho))
)
## End(Not run)
Compute "Child Behavior Checklist [Parent] (Syndrome Scale - Withdrawn/Depressed): Number missing"
Description
Computes the summary score mh_p_cbcl__synd__wthdep_nm
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): Number missing
-
Summarized variables:
-
mh_p_cbcl__wthdep__dep_001
-
mh_p_cbcl__wthdep__dep_002
-
mh_p_cbcl__wthdep__dep_003
-
mh_p_cbcl__wthdep_005
-
mh_p_cbcl__wthdep_001
-
mh_p_cbcl__wthdep_002
-
mh_p_cbcl__wthdep_003
-
mh_p_cbcl__wthdep_004
-
-
Excluded values:
777
999
Usage
vars_mh_p_cbcl__synd__wthdep
compute_mh_p_cbcl__synd__wthdep_nm(
data,
name = "mh_p_cbcl__synd__wthdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_p_cbcl__synd__wthdep
is vector of all column names
used to compute summary score of mh_p_cbcl__synd__wthdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_cbcl__synd__wthdep_nm(data) |>
select(
any_of(c("mh_p_cbcl__synd__wthdep_nm", vars_mh_p_cbcl__synd__wthdep))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Attuned): Mean"
Description
Computes the summary score mh_p_ders__attun_mean
Difficulties in Emotion Regulation Scale [Parent] (Attuned): Mean
-
Summarized variables:
-
mh_p_ders__attun_001
-
mh_p_ders__attun_002
-
mh_p_ders__attun_003
-
mh_p_ders__attun_004
-
mh_p_ders__attun_005
-
mh_p_ders__attun_006
-
-
Excluded values:
999
777
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_mh_p_ders__attun
compute_mh_p_ders__attun_mean(
data,
name = "mh_p_ders__attun_mean",
max_na = 1,
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_ders__attun
is vector of all column names
used to compute summary score of mh_p_ders__attun
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_ders__attun_mean(data) |>
select(
any_of(c("mh_p_ders__attun_mean", vars_mh_p_ders__attun))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Catastrophize): Mean"
Description
Computes the summary score mh_p_ders__catast_mean
Difficulties in Emotion Regulation Scale [Parent] (Catastrophize):
Mean
-
Summarized variables:
-
mh_p_ders__catast_001
-
mh_p_ders__catast_002
-
mh_p_ders__catast_003
-
mh_p_ders__catast_004
-
mh_p_ders__catast_005
-
mh_p_ders__catast_006
-
mh_p_ders__catast_007
-
mh_p_ders__catast_008
-
mh_p_ders__catast_009
-
mh_p_ders__catast_010
-
mh_p_ders__catast_011
-
mh_p_ders__catast_012
-
-
Excluded values:
999
777
-
Validation criterion: maximally 2 of 12 items missing
Usage
vars_mh_p_ders__catast
compute_mh_p_ders__catast_mean(
data,
name = "mh_p_ders__catast_mean",
max_na = 2,
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_ders__catast
is vector of all column names
used to compute summary score of mh_p_ders__catast
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_ders__catast_mean(data) |>
select(
any_of(c("mh_p_ders__catast_mean", vars_mh_p_ders__catast))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Distracted): Mean"
Description
Computes the summary score mh_p_ders__distract_mean
Difficulties in Emotion Regulation Scale [Parent] (Distracted): Mean
-
Summarized variables:
-
mh_p_ders__distract_001
-
mh_p_ders__distract_002
-
mh_p_ders__distract_003
-
mh_p_ders__distract_004
-
-
Excluded values:
999
777
-
Validation criterion: none of 4 items missing
Usage
vars_mh_p_ders__distract
compute_mh_p_ders__distract_mean(
data,
name = "mh_p_ders__distract_mean",
max_na = 0,
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_ders__distract
is vector of all column names
used to compute summary score of mh_p_ders__distract
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_ders__distract_mean(data) |>
select(
any_of(c("mh_p_ders__distract_mean", vars_mh_p_ders__distract))
)
## End(Not run)
Compute "Difficulties in Emotion Regulation Scale [Parent] (Negative Secondary): Mean"
Description
Computes the summary score mh_p_ders__negscnd_mean
Difficulties in Emotion Regulation Scale [Parent] (Negative
Secondary): Mean
-
Summarized variables:
-
mh_p_ders__negscnd_001
-
mh_p_ders__negscnd_002
-
mh_p_ders__negscnd_003
-
mh_p_ders__negscnd_004
-
mh_p_ders__negscnd_005
-
mh_p_ders__negscnd_006
-
mh_p_ders__negscnd_007
-
-
Excluded values:
999
777
-
Validation criterion: maximally 1 of 7 items missing
Usage
vars_mh_p_ders__negscnd
compute_mh_p_ders__negscnd_mean(
data,
name = "mh_p_ders__negscnd_mean",
max_na = 1,
exclude = c("999", "777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_ders__negscnd
is vector of all column names
used to compute summary score of mh_p_ders__negscnd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_ders__negscnd_mean(data) |>
select(
any_of(c("mh_p_ders__negscnd_mean", vars_mh_p_ders__negscnd))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Activation): Mean "
Description
Computes the summary score mh_p_eatq__actv_mean
Early Adolescent Temperament Questionnaire [Parent] (Activation): Mean
-
Summarized variables:
-
mh_p_eatq__actv_001
-
mh_p_eatq__actv_002
-
mh_p_eatq__actv_003
-
mh_p_eatq__actv_004
-
mh_p_eatq__actv_005
-
mh_p_eatq__actv_006
-
mh_p_eatq__actv_007
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 7 items missing
Usage
vars_mh_p_eatq__actv
compute_mh_p_eatq__actv_mean(
data,
name = "mh_p_eatq__actv_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__actv is a character vector of all column names
used to compute summary score of mh_p_eatq__actv_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__actv_mean(data)
select(
data,
any_of(c("mh_p_eatq__actv_mean", vars_mh_p_eatq__actv))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Affiliation): Mean"
Description
Computes the summary score mh_p_eatq__affl_mean
Early Adolescent Temperament Questionnaire [Parent] (Affiliation):
Mean
-
Summarized variables:
-
mh_p_eatq__affl_001
-
mh_p_eatq__affl_002
-
mh_p_eatq__affl_003
-
mh_p_eatq__affl_004
-
mh_p_eatq__affl_005
-
mh_p_eatq__affl_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_mh_p_eatq__affl
compute_mh_p_eatq__affl_mean(
data,
name = "mh_p_eatq__affl_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__affl is a character vector of all column names
used to compute summary score of mh_p_eatq__affl_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__affl_mean(data)
select(
data,
any_of(c("mh_p_eatq__affl_mean", vars_mh_p_eatq__affl))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Aggression): Mean"
Description
Computes the summary score mh_p_eatq__aggr_mean
Early Adolescent Temperament Questionnaire [Parent] (Aggression): Mean
-
Summarized variables:
-
mh_p_eatq__aggr_001
-
mh_p_eatq__aggr_002
-
mh_p_eatq__aggr_003
-
mh_p_eatq__aggr_004
-
mh_p_eatq__aggr_005
-
mh_p_eatq__aggr_006
-
mh_p_eatq__aggr_007
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 7 items missing
Usage
vars_mh_p_eatq__aggr
compute_mh_p_eatq__aggr_mean(
data,
name = "mh_p_eatq__aggr_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__aggr is a character vector of all column names
used to compute summary score of mh_p_eatq__aggr_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__aggr_mean(data)
select(
data,
any_of(c("mh_p_eatq__aggr_mean", vars_mh_p_eatq__aggr))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Attention): Mean"
Description
Computes the summary score mh_p_eatq__attn_mean
Early Adolescent Temperament Questionnaire [Parent] (Attention): Mean
-
Summarized variables:
-
mh_p_eatq__attn_001
-
mh_p_eatq__attn_002
-
mh_p_eatq__attn_003
-
mh_p_eatq__attn_004
-
mh_p_eatq__attn_005
-
mh_p_eatq__attn_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_mh_p_eatq__attn
compute_mh_p_eatq__attn_mean(
data,
name = "mh_p_eatq__attn_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__attn is a character vector of all column names
used to compute summary score of mh_p_eatq__attn_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__attn_mean(data)
select(
data,
any_of(c("mh_p_eatq__attn_mean", vars_mh_p_eatq__attn))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood): Mean"
Description
Computes the summary score mh_p_eatq__depm_mean
Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood):
Mean
-
Summarized variables:
-
mh_p_eatq__depm_001
-
mh_p_eatq__depm_002
-
mh_p_eatq__depm_003
-
mh_p_eatq__depm_004
-
mh_p_eatq__depm_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_mh_p_eatq__depm
compute_mh_p_eatq__depm_mean(
data,
name = "mh_p_eatq__depm_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__depm is a character vector of all column names
used to compute summary score of mh_p_eatq__depm_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__depm_mean(data)
select(
data,
any_of(c("mh_p_eatq__depm_mean", vars_mh_p_eatq__depm))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Fear): Mean"
Description
Computes the summary score mh_p_eatq__fear_mean
Early Adolescent Temperament Questionnaire [Parent] (Fear): Mean
-
Summarized variables:
-
mh_p_eatq__fear_001
-
mh_p_eatq__fear_002
-
mh_p_eatq__fear_003
-
mh_p_eatq__fear_004
-
mh_p_eatq__fear_005
-
mh_p_eatq__fear_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_mh_p_eatq__fear
compute_mh_p_eatq__fear_mean(
data,
name = "mh_p_eatq__fear_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__fear is a character vector of all column names
used to compute summary score of mh_p_eatq__fear_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__fear_mean(data)
select(
data,
any_of(c(
"mh_p_eatq__fear_mean",
vars_mh_p_eatq__fear
))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Frustration): Mean"
Description
Computes the summary score mh_p_eatq__frust_mean
Early Adolescent Temperament Questionnaire [Parent] (Frustration):
Mean
-
Summarized variables:
-
mh_p_eatq__frust_001
-
mh_p_eatq__frust_002
-
mh_p_eatq__frust_003
-
mh_p_eatq__frust_004
-
mh_p_eatq__frust_005
-
mh_p_eatq__frust_006
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 6 items missing
Usage
vars_mh_p_eatq__frust
compute_mh_p_eatq__frust_mean(
data,
name = "mh_p_eatq__frust_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__frust is a character vector of all column names
used to compute summary score of mh_p_eatq__frust_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__frust_mean(data)
select(
data,
any_of(c("mh_p_eatq__frust_mean", vars_mh_p_eatq__frust))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Inhibition): Mean"
Description
Computes the summary score mh_p_eatq__inhib_mean
Early Adolescent Temperament Questionnaire [Parent] (Inhibition): Mean
-
Summarized variables:
-
mh_p_eatq__inhib_001
-
mh_p_eatq__inhib_002
-
mh_p_eatq__inhib_003
-
mh_p_eatq__inhib_004
-
mh_p_eatq__inhib_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_mh_p_eatq__inhib
compute_mh_p_eatq__inhib_mean(
data,
name = "mh_p_eatq__inhib_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__inhib is a character vector of all column names
used to compute summary score of mh_p_eatq__inhib_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__inhib_mean(data)
select(
data,
any_of(c("mh_p_eatq__inhib_mean", vars_mh_p_eatq__inhib))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Shyness): Mean"
Description
Computes the summary score mh_p_eatq__shy_mean
Early Adolescent Temperament Questionnaire [Parent] (Shyness): Mean
-
Summarized variables:
-
mh_p_eatq__shy_001
-
mh_p_eatq__shy_002
-
mh_p_eatq__shy_003
-
mh_p_eatq__shy_004
-
mh_p_eatq__shy_005
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 5 items missing
Usage
vars_mh_p_eatq__shy
compute_mh_p_eatq__shy_mean(
data,
name = "mh_p_eatq__shy_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__shy is a character vector of all column names
used to compute summary score of mh_p_eatq__shy_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__shy_mean(data)
select(
data,
any_of(c(
"mh_p_eatq__shy_mean",
vars_mh_p_eatq__shy
))
)
## End(Not run)
Compute "Early Adolescent Temperament Questionnaire [Parent] (Surgency): Mean [Validation: No more than 1 missing or declined]"
Description
Computes the summary score mh_p_eatq__surg_mean
Early Adolescent Temperament Questionnaire [Parent] (Surgency): Mean
[Validation: No more than 1 missing or declined]
-
Summarized variables:
-
mh_p_eatq__surg_001
-
mh_p_eatq__surg_002
-
mh_p_eatq__surg_003
-
mh_p_eatq__surg_004
-
mh_p_eatq__surg_005
-
mh_p_eatq__surg_006
-
mh_p_eatq__surg_007
-
mh_p_eatq__surg_008
-
mh_p_eatq__surg_009
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 9 items missing
Usage
vars_mh_p_eatq__surg
compute_mh_p_eatq__surg_mean(
data,
name = "mh_p_eatq__surg_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
Format
vars_mh_p_eatq__surg is a character vector of all column names
used to compute summary score of mh_p_eatq__surg_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
data <- compute_mh_p_eatq__surg_mean(data)
select(
data,
any_of(c("mh_p_eatq__surg_mean", vars_mh_p_eatq__surg))
)
## End(Not run)
Compute "Parent General Behavior Inventory [Parent]: Number missing"
Description
Computes the summary score mh_p_gbi_nm
Parent General Behavior Inventory [Parent]: Number missing
-
Summarized variables:
-
mh_p_gbi_001
-
mh_p_gbi_002
-
mh_p_gbi_003
-
mh_p_gbi_004
-
mh_p_gbi_005
-
mh_p_gbi_006
-
mh_p_gbi_007
-
mh_p_gbi_008
-
mh_p_gbi_009
-
mh_p_gbi_010
-
-
Excluded values: none
Usage
vars_mh_p_gbi
compute_mh_p_gbi_nm(data, name = "mh_p_gbi_nm", exclude = NULL, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_gbi
is vector of all column names
used to compute summary score of mh_p_gbi
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_gbi_nm(data) |>
select(
any_of(c("mh_p_gbi_nm", vars_mh_p_gbi))
)
## End(Not run)
Compute "Life Events [Parent] (Events): Count [Validation: No more than 5 missing or declined]"
Description
Computes the summary score mh_p_ple_count
Life Events [Parent] (Events): Count [Validation: No more than 5
missing or declined]
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
vars_mh_p_ple
vars_mh_p_ple__exp
compute_mh_p_ple_count(
data,
name = "mh_p_ple_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Format
vars_mh_p_ple is a character vector of all column names
used to compute summary score of mh_p_ple
.
vars_mh_p_ple__exp is a character vector of all column names
used to compute summary score of mh_p_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_sum__v01
Life Events [Parent] (Severity of Good Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_p_ple__exp__v01
compute_mh_p_ple__severity__good_sum__v01(
data,
name = "mh_p_ple__severity__good_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__exp__v01 is a character vector of all column names
used to compute summary score of mh_p_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_sum__v02
Life Events [Parent] (Severity of Good Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
vars_mh_p_ple__exp__v02
compute_mh_p_ple__severity__good_sum__v02(
data,
name = "mh_p_ple__severity__good_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__exp__v02 is a character vector of all column names
used to compute summary score of mh_p_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Sum - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_sum__v03
Life Events [Parent] (Severity of Good Events): Sum - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_003
-
mh_p_ple__exp_004
-
mh_p_ple__exp_005
-
mh_p_ple__exp_006
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_009
-
mh_p_ple__exp_010
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_016
-
mh_p_ple__exp_017
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_020
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_025
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_029
-
mh_p_ple__exp_030
-
mh_p_ple__exp_031
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_p_ple__exp__v03
compute_mh_p_ple__severity__good_sum__v03(
data,
name = "mh_p_ple__severity__good_sum__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__exp__v03 is a character vector of all column names
used to compute summary score of mh_p_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity of Good Events): Sum - Version 4 (Starting at Year 7) [Validation: No more than 4 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity__good_sum__v04
Life Events [Parent] (Severity of Good Events): Sum - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__exp_001
-
mh_p_ple__exp_002
-
mh_p_ple__exp_007
-
mh_p_ple__exp_008
-
mh_p_ple__exp_011
-
mh_p_ple__exp_012
-
mh_p_ple__exp_013
-
mh_p_ple__exp_014
-
mh_p_ple__exp_015
-
mh_p_ple__exp_018
-
mh_p_ple__exp_019
-
mh_p_ple__exp_021
-
mh_p_ple__exp_022
-
mh_p_ple__exp_023
-
mh_p_ple__exp_024
-
mh_p_ple__exp_026
-
mh_p_ple__exp_027
-
mh_p_ple__exp_028
-
mh_p_ple__exp_032
-
mh_p_ple__exp_033
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
vars_mh_p_ple__exp__v04
compute_mh_p_ple__severity__good_sum__v04(
data,
name = "mh_p_ple__severity__good_sum__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Format
vars_mh_p_ple__exp__v04 is a character vector of all column names
used to compute summary score of mh_p_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Sum [Validation: No more than 5 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_sum
Life Events [Parent] (Severity): Sum [Validation: No more than 5
events missing and no severity items missing or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
vars_mh_p_ple__severity
compute_mh_p_ple__severity_sum(
data,
name = "mh_p_ple__severity_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Format
vars_mh_p_ple__severity is a character vector of all column names
used to compute summary score of mh_p_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_sum__v01
Life Events [Parent] (Severity): Sum - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_p_ple__severity__v01
compute_mh_p_ple__severity_sum__v01(
data,
name = "mh_p_ple__severity_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__severity__v01 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_sum__v02
Life Events [Parent] (Severity): Sum - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
vars_mh_p_ple__severity__v02
compute_mh_p_ple__severity_sum__v02(
data,
name = "mh_p_ple__severity_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__severity__v02 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Sum - Version 3 (Year 6 ) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_sum__v03
Life Events [Parent] (Severity): Sum - Version 3 (Year 6 )
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_003
-
mh_p_ple__severity_004
-
mh_p_ple__severity_005
-
mh_p_ple__severity_006
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_009
-
mh_p_ple__severity_010
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_016
-
mh_p_ple__severity_017
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_020
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_025
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_029
-
mh_p_ple__severity_030
-
mh_p_ple__severity_031
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_p_ple__severity__v03
compute_mh_p_ple__severity_sum__v03(
data,
name = "mh_p_ple__severity_sum__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__severity__v03 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Severity): Sum - Version 4 (Starting at Year 7) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_p_ple__severity_sum__v04
Life Events [Parent] (Severity): Sum - Version 4 (Starting at Year 7)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_p_ple__severity_001
-
mh_p_ple__severity_002
-
mh_p_ple__severity_007
-
mh_p_ple__severity_008
-
mh_p_ple__severity_011
-
mh_p_ple__severity_012
-
mh_p_ple__severity_013
-
mh_p_ple__severity_014
-
mh_p_ple__severity_015
-
mh_p_ple__severity_018
-
mh_p_ple__severity_019
-
mh_p_ple__severity_021
-
mh_p_ple__severity_022
-
mh_p_ple__severity_023
-
mh_p_ple__severity_024
-
mh_p_ple__severity_026
-
mh_p_ple__severity_027
-
mh_p_ple__severity_028
-
mh_p_ple__severity_032
-
mh_p_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
vars_mh_p_ple__severity__v04
compute_mh_p_ple__severity_sum__v04(
data,
name = "mh_p_ple__severity_sum__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Format
vars_mh_p_ple__severity__v04 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Count - Version 1 (Year 3) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_p_ple_count__v01
Life Events [Parent] (Events): Count - Version 1 (Year 3)
[Validation: No more than 6 missing or declined]
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_p_ple__v01
compute_mh_p_ple_count__v01(
data,
name = "mh_p_ple_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__v01 is a character vector of all column names
used to compute summary score of mh_p_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_p_ple_count__v02
Life Events [Parent] (Events): Count - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 missing or declined]
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
mh_p_ple_032
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 32 items missing
Usage
vars_mh_p_ple__v02
compute_mh_p_ple_count__v02(
data,
name = "mh_p_ple_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__v02 is a character vector of all column names
used to compute summary score of mh_p_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Count - Version 3 (Year 6 ) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_p_ple_count__v03
Life Events [Parent] (Events): Count - Version 3 (Year 6 )
[Validation: No more than 6 missing or declined]
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_003
-
mh_p_ple_004
-
mh_p_ple_005
-
mh_p_ple_006
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_009
-
mh_p_ple_010
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_016
-
mh_p_ple_017
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_020
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_025
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_029
-
mh_p_ple_030
-
mh_p_ple_031
-
mh_p_ple_032
-
mh_p_ple_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_p_ple__v03
compute_mh_p_ple_count__v03(
data,
name = "mh_p_ple_count__v03",
events = "ses-06A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_p_ple__v03 is a character vector of all column names
used to compute summary score of mh_p_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Parent] (Events): Count - Version 4 (Starting at Year 7) [Validation: No more than 4 missing or declined]"
Description
Computes the summary score mh_p_ple_count__v04
Life Events [Parent] (Events): Count - Version 4 (Starting at Year 7)
[Validation: No more than 4 missing or declined]
-
Summarized variables:
-
mh_p_ple_001
-
mh_p_ple_002
-
mh_p_ple_007
-
mh_p_ple_008
-
mh_p_ple_011
-
mh_p_ple_012
-
mh_p_ple_013
-
mh_p_ple_014
-
mh_p_ple_015
-
mh_p_ple_018
-
mh_p_ple_019
-
mh_p_ple_021
-
mh_p_ple_022
-
mh_p_ple_023
-
mh_p_ple_024
-
mh_p_ple_026
-
mh_p_ple_027
-
mh_p_ple_028
-
mh_p_ple_032
-
mh_p_ple_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 4 of 20 items missing
Usage
vars_mh_p_ple__v04
compute_mh_p_ple_count__v04(
data,
name = "mh_p_ple_count__v04",
events = "ses-07A",
combine = TRUE,
max_na = 4
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
Format
vars_mh_p_ple__v04 is a character vector of all column names
used to compute summary score of mh_p_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Short Social Responsiveness Scale [Parent]: Number missing"
Description
Computes the summary score mh_p_ssrs_nm
Short Social Responsiveness Scale [Parent]: Number missing
-
Summarized variables:
-
mh_p_ssrs_001
-
mh_p_ssrs_002
-
mh_p_ssrs_003
-
mh_p_ssrs_004
-
mh_p_ssrs_005
-
mh_p_ssrs_006
-
mh_p_ssrs_007
-
mh_p_ssrs_008
-
mh_p_ssrs_009
-
mh_p_ssrs_010
-
mh_p_ssrs_011
-
-
Excluded values: none
Usage
vars_mh_p_ssrs
compute_mh_p_ssrs_nm(
data,
name = "mh_p_ssrs_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_p_ssrs
is vector of all column names
used to compute summary score of mh_p_ssrs
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_p_ssrs_nm(data) |>
select(
any_of(c("mh_p_ssrs_nm", vars_mh_p_ssrs))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher]: Number missing"
Description
Computes the summary score mh_t_bpm_nm
Brief Problem Monitor [Teacher]: Number missing
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
Usage
vars_mh_t_bpm
compute_mh_t_bpm_nm(
data,
name = "mh_t_bpm_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_t_bpm
is vector of all column names
used to compute summary score of mh_t_bpm
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_t_bpm_nm(data) |>
select(
any_of(c("mh_t_bpm_nm", vars_mh_t_bpm))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Attention): Number missing"
Description
Computes the summary score mh_t_bpm__attn_nm
Brief Problem Monitor [Teacher] (Attention): Number missing
-
Summarized variables:
-
mh_t_bpm__attn_001
-
mh_t_bpm__attn_002
-
mh_t_bpm__attn_003
-
mh_t_bpm__attn_004
-
mh_t_bpm__attn_005
-
mh_t_bpm__attn_006
-
-
Excluded values:
777
999
Usage
vars_mh_t_bpm__attn
compute_mh_t_bpm__attn_nm(
data,
name = "mh_t_bpm__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_t_bpm__attn
is vector of all column names
used to compute summary score of mh_t_bpm__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_t_bpm__attn_nm(data) |>
select(
any_of(c("mh_t_bpm__attn_nm", vars_mh_t_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Externalizing): Number missing"
Description
Computes the summary score mh_t_bpm__ext_nm
Brief Problem Monitor [Teacher] (Externalizing): Number missing
-
Summarized variables:
-
mh_t_bpm__ext_001
-
mh_t_bpm__ext_002
-
mh_t_bpm__ext_003
-
mh_t_bpm__ext_004
-
mh_t_bpm__ext_005
-
mh_t_bpm__ext_006
-
-
Excluded values:
777
999
Usage
vars_mh_t_bpm__ext
compute_mh_t_bpm__ext_nm(
data,
name = "mh_t_bpm__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_t_bpm__ext
is vector of all column names
used to compute summary score of mh_t_bpm__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_t_bpm__ext_nm(data) |>
select(
any_of(c("mh_t_bpm__ext_nm", vars_mh_t_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Teacher] (Internalizing): Number missing"
Description
Computes the summary score mh_t_bpm__int_nm
Brief Problem Monitor [Teacher] (Internalizing): Number missing
-
Summarized variables:
-
mh_t_bpm__int_001
-
mh_t_bpm__int_002
-
mh_t_bpm__int_003
-
mh_t_bpm__int_004
-
mh_t_bpm__int_005
-
mh_t_bpm__int_006
-
-
Excluded values:
777
999
Usage
vars_mh_t_bpm__int
compute_mh_t_bpm__int_nm(
data,
name = "mh_t_bpm__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_t_bpm__int
is vector of all column names
used to compute summary score of mh_t_bpm__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_t_bpm__int_nm(data) |>
select(
any_of(c("mh_t_bpm__int_nm", vars_mh_t_bpm__int))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Drive): Number missing"
Description
Computes the summary score mh_y_bisbas__bas__dr_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Drive): Number missing
-
Summarized variables:
-
mh_y_bisbas__bas__dr_001
-
mh_y_bisbas__bas__dr_002
-
mh_y_bisbas__bas__dr_003
-
mh_y_bisbas__bas__dr_004
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bas__dr
compute_mh_y_bisbas__bas__dr_nm(
data,
name = "mh_y_bisbas__bas__dr_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bas__dr
is vector of all column names
used to compute summary score of mh_y_bisbas__bas__dr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bas__dr_nm(data) |>
select(
any_of(c("mh_y_bisbas__bas__dr_nm", vars_mh_y_bisbas__bas__dr))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Fun Seeking): Number missing"
Description
Computes the summary score mh_y_bisbas__bas__fs_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Fun Seeking): Number missing
-
Summarized variables:
-
mh_y_bisbas__bas__fs_001
-
mh_y_bisbas__bas__fs_002
-
mh_y_bisbas__bas__fs_003
-
mh_y_bisbas__bas__fs_004
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bas__fs
compute_mh_y_bisbas__bas__fs_nm(
data,
name = "mh_y_bisbas__bas__fs_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bas__fs
is vector of all column names
used to compute summary score of mh_y_bisbas__bas__fs
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bas__fs_nm(data) |>
select(
any_of(c("mh_y_bisbas__bas__fs_nm", vars_mh_y_bisbas__bas__fs))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BAS Reward Responsiveness): Number missing"
Description
Computes the summary score mh_y_bisbas__bas__rr_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Reward Responsiveness): Number missing
-
Summarized variables:
-
mh_y_bisbas__bas__rr_001
-
mh_y_bisbas__bas__rr_002
-
mh_y_bisbas__bas__rr_003
-
mh_y_bisbas__bas__rr_004
-
mh_y_bisbas__bas__rr_005
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bas__rr
compute_mh_y_bisbas__bas__rr_nm(
data,
name = "mh_y_bisbas__bas__rr_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bas__rr
is vector of all column names
used to compute summary score of mh_y_bisbas__bas__rr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bas__rr_nm(data) |>
select(
any_of(c("mh_y_bisbas__bas__rr_nm", vars_mh_y_bisbas__bas__rr))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] ((BAS Reward Responsiveness (modified)): Number missing"
Description
Computes the summary score mh_y_bisbas__bas__rr_nm__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] ((BAS Reward Responsiveness (modified)): Number missing
-
Summarized variables:
-
mh_y_bisbas__bas__rr_001
-
mh_y_bisbas__bas__rr_002
-
mh_y_bisbas__bas__rr_004
-
mh_y_bisbas__bas__rr_005
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bas__rr__v01
compute_mh_y_bisbas__bas__rr_nm__v01(
data,
name = "mh_y_bisbas__bas__rr_nm__v01",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bas__rr__v01
is vector of all column names
used to compute summary score of mh_y_bisbas__bas__rr__v01
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bas__rr_nm__v01(data) |>
select(
any_of(c("mh_y_bisbas__bas__rr_nm__v01", vars_mh_y_bisbas__bas__rr__v01))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BIS): Number missing"
Description
Computes the summary score mh_y_bisbas__bis_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS): Number missing
-
Summarized variables:
-
mh_y_bisbas__bis_001
-
mh_y_bisbas__bis_002
-
mh_y_bisbas__bis_003
-
mh_y_bisbas__bis_004
-
mh_y_bisbas__bis_005
-
mh_y_bisbas__bis_006
-
mh_y_bisbas__bis_007
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bis
compute_mh_y_bisbas__bis_nm(
data,
name = "mh_y_bisbas__bis_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bis
is vector of all column names
used to compute summary score of mh_y_bisbas__bis
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bis_nm(data) |>
select(
any_of(c("mh_y_bisbas__bis_nm", vars_mh_y_bisbas__bis))
)
## End(Not run)
Compute "The Behavioral Inhibition System/Behavioral Activation System Scales [Youth] (BIS (modified)): Number missing"
Description
Computes the summary score mh_y_bisbas__bis_nm__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS (modified)): Number missing
-
Summarized variables:
-
mh_y_bisbas__bis_002
-
mh_y_bisbas__bis_003
-
mh_y_bisbas__bis_004
-
mh_y_bisbas__bis_006
-
-
Excluded values: none
Usage
vars_mh_y_bisbas__bis__v01
compute_mh_y_bisbas__bis_nm__v01(
data,
name = "mh_y_bisbas__bis_nm__v01",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_bisbas__bis__v01
is vector of all column names
used to compute summary score of mh_y_bisbas__bis__v01
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bisbas__bis_nm__v01(data) |>
select(
any_of(c("mh_y_bisbas__bis_nm__v01", vars_mh_y_bisbas__bis__v01))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth]: Number missing"
Description
Computes the summary score mh_y_bpm_nm
Brief Problem Monitor [Youth]: Number missing
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
Usage
vars_mh_y_bpm
compute_mh_y_bpm_nm(
data,
name = "mh_y_bpm_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_bpm
is vector of all column names
used to compute summary score of mh_y_bpm
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bpm_nm(data) |>
select(
any_of(c("mh_y_bpm_nm", vars_mh_y_bpm))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Attention): Number missing"
Description
Computes the summary score mh_y_bpm__attn_nm
Brief Problem Monitor [Youth] (Attention): Number missing
-
Summarized variables:
-
mh_y_bpm__attn_001
-
mh_y_bpm__attn_002
-
mh_y_bpm__attn_003
-
mh_y_bpm__attn_004
-
mh_y_bpm__attn_005
-
mh_y_bpm__attn_006
-
-
Excluded values:
777
999
Usage
vars_mh_y_bpm__attn
compute_mh_y_bpm__attn_nm(
data,
name = "mh_y_bpm__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_bpm__attn
is vector of all column names
used to compute summary score of mh_y_bpm__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bpm__attn_nm(data) |>
select(
any_of(c("mh_y_bpm__attn_nm", vars_mh_y_bpm__attn))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Externalizing): Number missing"
Description
Computes the summary score mh_y_bpm__ext_nm
Brief Problem Monitor [Youth] (Externalizing): Number missing
-
Summarized variables:
-
mh_y_bpm__ext_001
-
mh_y_bpm__ext_002
-
mh_y_bpm__ext_003
-
mh_y_bpm__ext_004
-
mh_y_bpm__ext_005
-
mh_y_bpm__ext_006
-
mh_y_bpm__ext_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_bpm__ext
compute_mh_y_bpm__ext_nm(
data,
name = "mh_y_bpm__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_bpm__ext
is vector of all column names
used to compute summary score of mh_y_bpm__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bpm__ext_nm(data) |>
select(
any_of(c("mh_y_bpm__ext_nm", vars_mh_y_bpm__ext))
)
## End(Not run)
Compute "Brief Problem Monitor [Youth] (Internalizing): Number missing"
Description
Computes the summary score mh_y_bpm__int_nm
Brief Problem Monitor [Youth] (Internalizing): Number missing
-
Summarized variables:
-
mh_y_bpm__int_001
-
mh_y_bpm__int_002
-
mh_y_bpm__int_003
-
mh_y_bpm__int_004
-
mh_y_bpm__int_005
-
mh_y_bpm__int_006
-
-
Excluded values:
777
999
Usage
vars_mh_y_bpm__int
compute_mh_y_bpm__int_nm(
data,
name = "mh_y_bpm__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_bpm__int
is vector of all column names
used to compute summary score of mh_y_bpm__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_bpm__int_nm(data) |>
select(
any_of(c("mh_y_bpm__int_nm", vars_mh_y_bpm__int))
)
## End(Not run)
Compute "Emotion Regulation Questionnaire [Youth] (Reappraisal): Mean"
Description
Computes the summary score mh_y_erq__reapp_mean
Emotion Regulation Questionnaire [Youth] (Reappraisal): Mean
-
Summarized variables:
-
mh_y_erq__reapp_001
-
mh_y_erq__reapp_002
-
mh_y_erq__reapp_003
-
-
Excluded values:
777
-
Validation criterion: none of 3 items missing
Usage
vars_mh_y_erq__reapp
compute_mh_y_erq__reapp_mean(
data,
name = "mh_y_erq__reapp_mean",
max_na = 0,
exclude = c("777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_erq__reapp
is vector of all column names
used to compute summary score of mh_y_erq__reapp
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_erq__reapp_mean(data) |>
select(
any_of(c("mh_y_erq__reapp_mean", vars_mh_y_erq__reapp))
)
## End(Not run)
Compute "Emotion Regulation Questionnaire [Youth] (Suppression): Mean"
Description
Computes the summary score mh_y_erq__suppr_mean
Emotion Regulation Questionnaire [Youth] (Suppression): Mean
-
Summarized variables:
-
mh_y_erq__suppr_001
-
mh_y_erq__suppr_002
-
mh_y_erq__suppr_003
-
-
Excluded values:
777
-
Validation criterion: none of 3 items missing
Usage
vars_mh_y_erq__suppr
compute_mh_y_erq__suppr_mean(
data,
name = "mh_y_erq__suppr_mean",
max_na = 0,
exclude = c("777"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_erq__suppr
is vector of all column names
used to compute summary score of mh_y_erq__suppr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_erq__suppr_mean(data) |>
select(
any_of(c("mh_y_erq__suppr_mean", vars_mh_y_erq__suppr))
)
## End(Not run)
Compute "NIH Toolbox - Positive Affect Items [Youth] (NA): Number missing"
Description
Computes the summary score mh_y_pai_nm
NIH Toolbox - Positive Affect Items [Youth] (NA): Number missing
-
Summarized variables:
-
mh_y_pai_001
-
mh_y_pai_002
-
mh_y_pai_003
-
mh_y_pai_004
-
mh_y_pai_005
-
mh_y_pai_006
-
mh_y_pai_007
-
mh_y_pai_008
-
mh_y_pai_009
-
-
Excluded values:
777
999
Usage
vars_mh_y_pai
compute_mh_y_pai_nm(
data,
name = "mh_y_pai_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_pai
is vector of all column names
used to compute summary score of compute_mh_y_pai
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_pai_nm(data) |>
select(
any_of(c("mh_y_pai_nm", vars_mh_y_pai))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Overt Aggression): Number missing"
Description
Computes the summary score mh_y_peq__overt__agg_nm
Peer Experiences Questionnaire [Youth] (Overt Aggression): Number
missing
-
Summarized variables:
-
mh_y_peq__overt__agg_001
-
mh_y_peq__overt__agg_002
-
mh_y_peq__overt__agg_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__overt__agg
compute_mh_y_peq__overt__agg_nm(
data,
name = "mh_y_peq__overt__agg_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__overt__agg
is vector of all column names
used to compute summary score of mh_y_peq__overt__agg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__overt__agg_nm(data) |>
select(
any_of(c("mh_y_peq__overt__agg_nm", vars_mh_y_peq__overt__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Overt Victimization): Number missing"
Description
Computes the summary score mh_y_peq__overt__vict_nm
Peer Experiences Questionnaire [Youth] (Overt Victimization): Number
missing
-
Summarized variables:
-
mh_y_peq__overt__vict_001
-
mh_y_peq__overt__vict_002
-
mh_y_peq__overt__vict_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__overt__vict
compute_mh_y_peq__overt__vict_nm(
data,
name = "mh_y_peq__overt__vict_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__overt__vict
is vector of all column names
used to compute summary score of mh_y_peq__overt__vict
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__overt__vict_nm(data) |>
select(
any_of(c("mh_y_peq__overt__vict_nm", vars_mh_y_peq__overt__vict))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Relational Aggression): Number missing"
Description
Computes the summary score mh_y_peq__rel__agg_nm
Peer Experiences Questionnaire [Youth] (Relational Aggression): Number
missing
-
Summarized variables:
-
mh_y_peq__rel__agg_001
-
mh_y_peq__rel__agg_002
-
mh_y_peq__rel__agg_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__rel__agg
compute_mh_y_peq__rel__agg_nm(
data,
name = "mh_y_peq__rel__agg_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__rel__agg
is vector of all column names
used to compute summary score of mh_y_peq__rel__agg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__rel__agg_nm(data) |>
select(
any_of(c("mh_y_peq__rel__agg_nm", vars_mh_y_peq__rel__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Relational Victimization): Number missing"
Description
Computes the summary score mh_y_peq__rel__vict_nm
Peer Experiences Questionnaire [Youth] (Relational Victimization):
Number missing
-
Summarized variables:
-
mh_y_peq__rel__vict_001
-
mh_y_peq__rel__vict_002
-
mh_y_peq__rel__vict_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__rel__vict
compute_mh_y_peq__rel__vict_nm(
data,
name = "mh_y_peq__rel__vict_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__rel__vict
is vector of all column names
used to compute summary score of mh_y_peq__rel__vict
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__rel__vict_nm(data) |>
select(
any_of(c("mh_y_peq__rel__vict_nm", vars_mh_y_peq__rel__vict))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Reputational Aggression): Number missing"
Description
Computes the summary score mh_y_peq__rep__agg_nm
Peer Experiences Questionnaire [Youth] (Reputational Aggression):
Number missing
-
Summarized variables:
-
mh_y_peq__rep__agg_001
-
mh_y_peq__rep__agg_002
-
mh_y_peq__rep__agg_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__rep__agg
compute_mh_y_peq__rep__agg_nm(
data,
name = "mh_y_peq__rep__agg_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__rep__agg
is vector of all column names
used to compute summary score of mh_y_peq__rep__agg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__rep__agg_nm(data) |>
select(
any_of(c("mh_y_peq__rep__agg_nm", vars_mh_y_peq__rep__agg))
)
## End(Not run)
Compute "Peer Experiences Questionnaire [Youth] (Reputational Victimization): Number missing"
Description
Computes the summary score mh_y_peq__rep__vict_nm
Peer Experiences Questionnaire [Youth] (Reputational Victimization):
Number missing
-
Summarized variables:
-
mh_y_peq__rep__vict_001
-
mh_y_peq__rep__vict_002
-
mh_y_peq__rep__vict_003
-
-
Excluded values: none
Usage
vars_mh_y_peq__rep__vict
compute_mh_y_peq__rep__vict_nm(
data,
name = "mh_y_peq__rep__vict_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_peq__rep__vict
is vector of all column names
used to compute summary score of mh_y_peq__rep__vict
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_peq__rep__vict_nm(data) |>
select(
any_of(c("mh_y_peq__rep__vict_nm", vars_mh_y_peq__rep__vict))
)
## End(Not run)
Compute "Life Events [Youth] (Events): Count [Validation: No more than 5 missing or declined]"
Description
Computes the summary score mh_y_ple_count
Life Events [Youth] (Events): Count [Validation: No more than 5
missing or declined]
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
vars_mh_y_ple
compute_mh_y_ple_count(
data,
name = "mh_y_ple_count",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Format
vars_mh_y_ple is a character vector of all column names
used to compute summary score of mh_y_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Sum [Validation: No more than 5 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_sum
Life Events [Youth] (Severity of Good Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
vars_mh_y_ple__exp
compute_mh_y_ple__severity__good_sum(
data,
name = "mh_y_ple__severity__good_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Format
vars_mh_y_ple__exp is a character vector of all column names
used to compute summary score of mh_y_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_sum__v01
Life Events [Youth] (Severity of Good Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_y_ple__exp__v01
compute_mh_y_ple__severity__good_sum__v01(
data,
name = "mh_y_ple__severity__good_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__exp__v01 is a character vector of all column names
used to compute summary score of mh_y_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_sum__v02
Life Events [Youth] (Severity of Good Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_y_ple__exp__v02
compute_mh_y_ple__severity__good_sum__v02(
data,
name = "mh_y_ple__severity__good_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__exp__v02 is a character vector of all column names
used to compute summary score of mh_y_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity of Good Events): Sum - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no experience/severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity__good_sum__v03
Life Events [Youth] (Severity of Good Events): Sum - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__exp_001
-
mh_y_ple__exp_002
-
mh_y_ple__exp_003
-
mh_y_ple__exp_004
-
mh_y_ple__exp_005
-
mh_y_ple__exp_006
-
mh_y_ple__exp_007
-
mh_y_ple__exp_008
-
mh_y_ple__exp_009
-
mh_y_ple__exp_010
-
mh_y_ple__exp_011
-
mh_y_ple__exp_012
-
mh_y_ple__exp_013
-
mh_y_ple__exp_014
-
mh_y_ple__exp_015
-
mh_y_ple__exp_016
-
mh_y_ple__exp_017
-
mh_y_ple__exp_018
-
mh_y_ple__exp_019
-
mh_y_ple__exp_020
-
mh_y_ple__exp_021
-
mh_y_ple__exp_022
-
mh_y_ple__exp_023
-
mh_y_ple__exp_024
-
mh_y_ple__exp_025
-
mh_y_ple__exp_026
-
mh_y_ple__exp_027
-
mh_y_ple__exp_028
-
mh_y_ple__exp_029
-
mh_y_ple__exp_030
-
mh_y_ple__exp_031
-
mh_y_ple__exp_032
-
mh_y_ple__exp_033
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_y_ple__exp__v03
compute_mh_y_ple__severity__good_sum__v03(
data,
name = "mh_y_ple__severity__good_sum__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__exp__v03 is a character vector of all column names
used to compute summary score of mh_y_ple__exp
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Sum [Validation: No more than 5 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_sum
Life Events [Youth] (Severity): Sum [Validation: No more than 5
events missing and no severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 5 of 25 items missing
Usage
vars_mh_y_ple__severity
compute_mh_y_ple__severity_sum(
data,
name = "mh_y_ple__severity_sum",
combine = TRUE,
max_na = 5
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
Format
vars_mh_y_ple__severity is a character vector of all column names
used to compute summary score of mh_y_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Sum - Version 1 (Year 3) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_sum__v01
Life Events [Youth] (Severity): Sum - Version 1 (Year 3) [Validation:
No more than 6 events missing and no severity items missing or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_y_ple__severity__v01
compute_mh_y_ple__severity_sum__v01(
data,
name = "mh_y_ple__severity_sum__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__severity__v01 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Sum - Version 2 (Year 4 and Year 5) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_sum__v02
Life Events [Youth] (Severity): Sum - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_y_ple__severity__v02
compute_mh_y_ple__severity_sum__v02(
data,
name = "mh_y_ple__severity_sum__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__severity__v02 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Severity): Sum - Version 3 (Starting at Year 6) [Validation: No more than 6 events missing and no severity items missing or declined]"
Description
Computes the summary score mh_y_ple__severity_sum__v03
Life Events [Youth] (Severity): Sum - Version 3 (Starting at Year 6)
[Validation: No more than 6 events missing and no severity items missing
or declined]
-
Summarized variables:
-
mh_y_ple__severity_001
-
mh_y_ple__severity_002
-
mh_y_ple__severity_003
-
mh_y_ple__severity_004
-
mh_y_ple__severity_005
-
mh_y_ple__severity_006
-
mh_y_ple__severity_007
-
mh_y_ple__severity_008
-
mh_y_ple__severity_009
-
mh_y_ple__severity_010
-
mh_y_ple__severity_011
-
mh_y_ple__severity_012
-
mh_y_ple__severity_013
-
mh_y_ple__severity_014
-
mh_y_ple__severity_015
-
mh_y_ple__severity_016
-
mh_y_ple__severity_017
-
mh_y_ple__severity_018
-
mh_y_ple__severity_019
-
mh_y_ple__severity_020
-
mh_y_ple__severity_021
-
mh_y_ple__severity_022
-
mh_y_ple__severity_023
-
mh_y_ple__severity_024
-
mh_y_ple__severity_025
-
mh_y_ple__severity_026
-
mh_y_ple__severity_027
-
mh_y_ple__severity_028
-
mh_y_ple__severity_029
-
mh_y_ple__severity_030
-
mh_y_ple__severity_031
-
mh_y_ple__severity_032
-
mh_y_ple__severity_033
-
mh_y_ple__severity_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 34 items missing
Usage
vars_mh_y_ple__severity__v03
compute_mh_y_ple__severity_sum__v03(
data,
name = "mh_y_ple__severity_sum__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__severity__v03 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Count - Version 1 (Year 3) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_y_ple_count__v01
Life Events [Youth] (Events): Count - Version 1 (Year 3) [Validation:
No more than 6 missing or declined]
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 31 items missing
Usage
vars_mh_y_ple__v01
compute_mh_y_ple_count__v01(
data,
name = "mh_y_ple_count__v01",
events = "ses-03A",
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__v01 is a character vector of all column names
used to compute summary score of mh_y_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Count - Version 2 (Year 4 and Year 5) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_y_ple_count__v02
Life Events [Youth] (Events): Count - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 missing or declined]
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
mh_y_ple_032
-
mh_y_ple_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 33 items missing
Usage
vars_mh_y_ple__v02
compute_mh_y_ple_count__v02(
data,
name = "mh_y_ple_count__v02",
events = c("ses-04A", "ses-05A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__v02 is a character vector of all column names
used to compute summary score of mh_y_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Life Events [Youth] (Events): Count - Version 3 (Starting at Year 6) [Validation: No more than 6 missing or declined]"
Description
Computes the summary score mh_y_ple_count__v03
Life Events [Youth] (Events): Count - Version 3 (Starting at Year 6)
[Validation: No more than 6 missing or declined]
-
Summarized variables:
-
mh_y_ple_001
-
mh_y_ple_002
-
mh_y_ple_003
-
mh_y_ple_004
-
mh_y_ple_005
-
mh_y_ple_006
-
mh_y_ple_007
-
mh_y_ple_008
-
mh_y_ple_009
-
mh_y_ple_010
-
mh_y_ple_011
-
mh_y_ple_012
-
mh_y_ple_013
-
mh_y_ple_014
-
mh_y_ple_015
-
mh_y_ple_016
-
mh_y_ple_017
-
mh_y_ple_018
-
mh_y_ple_019
-
mh_y_ple_020
-
mh_y_ple_021
-
mh_y_ple_022
-
mh_y_ple_023
-
mh_y_ple_024
-
mh_y_ple_025
-
mh_y_ple_026
-
mh_y_ple_027
-
mh_y_ple_028
-
mh_y_ple_029
-
mh_y_ple_030
-
mh_y_ple_031
-
mh_y_ple_032
-
mh_y_ple_033
-
mh_y_ple_034
-
-
Excluded values:
444
777
999
-
Validation criterion: maximally 6 of 34 items missing
Usage
vars_mh_y_ple__v03
compute_mh_y_ple_count__v03(
data,
name = "mh_y_ple_count__v03",
events = c("ses-06A", "ses-07A"),
combine = TRUE,
max_na = 6
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
Format
vars_mh_y_ple__v03 is a character vector of all column names
used to compute summary score of mh_y_ple
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Prodromal Psychosis Scale [Youth] (Bother responses): Number missing"
Description
Computes the summary score mh_y_pps__bother_nm
Prodromal Psychosis Scale [Youth] (Bother responses): Number missing
-
Summarized variables:
-
mh_y_pps__bother_001
-
mh_y_pps__bother_002
-
mh_y_pps__bother_003
-
mh_y_pps__bother_004
-
mh_y_pps__bother_005
-
mh_y_pps__bother_006
-
mh_y_pps__bother_007
-
mh_y_pps__bother_008
-
mh_y_pps__bother_009
-
mh_y_pps__bother_010
-
mh_y_pps__bother_011
-
mh_y_pps__bother_012
-
mh_y_pps__bother_013
-
mh_y_pps__bother_014
-
mh_y_pps__bother_015
-
mh_y_pps__bother_016
-
mh_y_pps__bother_017
-
mh_y_pps__bother_018
-
mh_y_pps__bother_019
-
mh_y_pps__bother_020
-
mh_y_pps__bother_021
-
Usage
vars_mh_y_pps__bother
compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_mh_y_pps__bother is a character vector of all
column names used to compute summary of mh_y_pps__bother
scores.
Details
The number of missing values in the mh_y_pps__bother
score is
calculated by subtracting the number of valid pairs from the total
PPS count for each subject (mh_y_pps_count - bother_pair_good_sum).
A good pair is defined as a pair where the mh_y_pps_count
is 1 and
the mh_y_pps__bother
is not missing.
See Also
Examples
## Not run:
compute_mh_y_pps__bother_nm(data) |>
select(
any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother))
)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (Severity Score): Number missing"
Description
Computes the summary score mh_y_pps__severity_nm
Prodromal Psychosis Scale [Youth] (Severity Score): Number missing
-
Summarized variables:
-
mh_y_pps__severity_001
-
mh_y_pps__severity_002
-
mh_y_pps__severity_003
-
mh_y_pps__severity_004
-
mh_y_pps__severity_005
-
mh_y_pps__severity_006
-
mh_y_pps__severity_007
-
mh_y_pps__severity_008
-
mh_y_pps__severity_009
-
mh_y_pps__severity_010
-
mh_y_pps__severity_011
-
mh_y_pps__severity_012
-
mh_y_pps__severity_013
-
mh_y_pps__severity_014
-
mh_y_pps__severity_015
-
mh_y_pps__severity_016
-
mh_y_pps__severity_017
-
mh_y_pps__severity_018
-
mh_y_pps__severity_019
-
mh_y_pps__severity_020
-
mh_y_pps__severity_021
-
-
Excluded values: none
Usage
vars_mh_y_pps__severity
compute_mh_y_pps__severity_nm(
data,
name = "mh_y_pps__severity_nm",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_mh_y_pps__severity is a character vector of all column names
used to compute summary of mh_y_pps__severity
scores.
Details
The number of missing values in the mh_y_pps__severity
score is
calculated by subtracting the number of valid pairs from the total
bother count for each subject
(mh_y_pps__bother_yes_count - severity_pair_good_sum).
A good pair is defined as a pair where the mh_y_pps__bother__yes_count
is 1 and the mh_y_pps__severity
is not missing.
See Also
compute_mh_y_pps__bother__yes_count()
Examples
## Not run:
compute_mh_y_pps__severity_nm(data) |>
select(
any_of(c("mh_y_pps__severity_nm", vars_mh_y_pps__severity))
)
## End(Not run)
Compute "Prodromal Psychosis Scale [Youth] (number of "Yes" responses): Count "
Description
Computes the summary score mh_y_pps_count
Prodromal Psychosis Scale [Youth] (number of
-
Summarized variables:
-
mh_y_pps_001
-
mh_y_pps_002
-
mh_y_pps_003
-
mh_y_pps_004
-
mh_y_pps_005
-
mh_y_pps_006
-
mh_y_pps_007
-
mh_y_pps_008
-
mh_y_pps_009
-
mh_y_pps_010
-
mh_y_pps_011
-
mh_y_pps_012
-
mh_y_pps_013
-
mh_y_pps_014
-
mh_y_pps_015
-
mh_y_pps_016
-
mh_y_pps_017
-
mh_y_pps_018
-
mh_y_pps_019
-
mh_y_pps_020
-
mh_y_pps_021
-
-
Excluded values: none
-
Validation criterion: maximally 4 of 21 items missing
Usage
vars_mh_y_pps_count
compute_mh_y_pps_count(
data,
name = "mh_y_pps_count",
max_na = 4,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Format
vars_mh_y_pps_count is a character vector of all column names
used to compute summary score of mh_y_pps_count
and mh_y_pps_nm
Details
The mh_y_pps_count
is calculated by summing the number of 1
s in each
question. If the number of missing values is greater than max_na
,
the summary score is set to NA
. By default, max_na
is set to 4 (20%).
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_mh_y_pps_count(data) |>
select(
any_of(c("mh_y_pps_count", vars_mh_y_pps_count))
)
## End(Not run)
Compute "7-Up Mania Inventory [Youth]: Number missing"
Description
Computes the summary score mh_y_sup_nm
7-Up Mania Inventory [Youth]: Number missing
-
Summarized variables:
-
mh_y_sup_001
-
mh_y_sup_002
-
mh_y_sup_003
-
mh_y_sup_004
-
mh_y_sup_005
-
mh_y_sup_006
-
mh_y_sup_007
-
-
Excluded values: none
Usage
vars_mh_y_sup
compute_mh_y_sup_nm(data, name = "mh_y_sup_nm", exclude = NULL, combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_sup
is vector of all column names
used to compute summary score of mh_y_sup
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_sup_nm(data) |>
select(
any_of(c("mh_y_sup_nm", vars_mh_y_sup))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative Urgency): Number missing"
Description
Computes the summary score mh_y_upps__nurg_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative
Urgency): Number missing
-
Summarized variables:
-
mh_y_upps__nurg_001
-
mh_y_upps__nurg_002
-
mh_y_upps__nurg_003
-
mh_y_upps__nurg_004
-
-
Excluded values: none
Usage
vars_mh_y_upps__nurg
compute_mh_y_upps__nurg_nm(
data,
name = "mh_y_upps__nurg_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_upps__nurg
is vector of all column names
used to compute summary score of mh_y_upps__nurg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_upps__nurg_nm(data) |>
select(
any_of(c("mh_y_upps__nurg_nm", vars_mh_y_upps__nurg))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of Perseverance (GSSF)): Number missing"
Description
Computes the summary score mh_y_upps__pers_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Perseverance (GSSF)): Number missing
-
Summarized variables:
-
mh_y_upps__pers_001
-
mh_y_upps__pers_002
-
mh_y_upps__pers_003
-
mh_y_upps__pers_004
-
-
Excluded values: none
Usage
vars_mh_y_upps__pers
compute_mh_y_upps__pers_nm(
data,
name = "mh_y_upps__pers_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_upps__pers
is vector of all column names
used to compute summary score of mh_y_upps__pers
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_upps__pers_nm(data) |>
select(
any_of(c("mh_y_upps__pers_nm", vars_mh_y_upps__pers))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of Planning): Number missing"
Description
Computes the summary score mh_y_upps__plan_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Planning): Number missing
-
Summarized variables:
-
mh_y_upps__plan_001
-
mh_y_upps__plan_002
-
mh_y_upps__plan_003
-
mh_y_upps__plan_004
-
-
Excluded values: none
Usage
vars_mh_y_upps__plan
compute_mh_y_upps__plan_nm(
data,
name = "mh_y_upps__plan_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_upps__plan
is vector of all column names
used to compute summary score of mh_y_upps__plan
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_upps__plan_nm(data) |>
select(
any_of(c("mh_y_upps__plan_nm", vars_mh_y_upps__plan))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive Urgency): Number missing"
Description
Computes the summary score mh_y_upps__purg_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive
Urgency): Number missing
-
Summarized variables:
-
mh_y_upps__purg_001
-
mh_y_upps__purg_002
-
mh_y_upps__purg_003
-
mh_y_upps__purg_004
-
-
Excluded values: none
Usage
vars_mh_y_upps__purg
compute_mh_y_upps__purg_nm(
data,
name = "mh_y_upps__purg_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_upps__purg
is vector of all column names
used to compute summary score of mh_y_upps__purg
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_upps__purg_nm(data) |>
select(
any_of(c("mh_y_upps__purg_nm", vars_mh_y_upps__purg))
)
## End(Not run)
Compute "Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation Seeking): Number missing"
Description
Computes the summary score mh_y_upps__sens_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation
Seeking): Number missing
-
Summarized variables:
-
mh_y_upps__sens_001
-
mh_y_upps__sens_002
-
mh_y_upps__sens_003
-
mh_y_upps__sens_004
-
-
Excluded values: none
Usage
vars_mh_y_upps__sens
compute_mh_y_upps__sens_nm(
data,
name = "mh_y_upps__sens_nm",
exclude = NULL,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_mh_y_upps__sens
is vector of all column names
used to compute summary score of mh_y_upps__sens
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_upps__sens_nm(data) |>
select(
any_of(c("mh_y_upps__sens_nm", vars_mh_y_upps__sens))
)
## End(Not run)
Compute "Youth Self Report [Youth]: Number missing"
Description
Computes the summary score mh_y_ysr_nm
Youth Self Report [Youth]: Number missing
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn_004
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule_005
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som_001
-
mh_y_ysr__othpr_001
-
mh_y_ysr__othpr_002
-
mh_y_ysr__othpr_003
-
mh_y_ysr__othpr_004
-
mh_y_ysr__othpr_005
-
mh_y_ysr__othpr_006
-
mh_y_ysr__othpr_007
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr
compute_mh_y_ysr_nm(
data,
name = "mh_y_ysr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr
is vector of all column names
used to compute summary score of mh_y_ysr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr_nm(data) |>
select(
any_of(c("mh_y_ysr_nm", vars_mh_y_ysr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__adhd_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Number
missing
-
Summarized variables:
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn__adhd_005
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__adhd
compute_mh_y_ysr__dsm__adhd_nm(
data,
name = "mh_y_ysr__dsm__adhd_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__adhd
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__adhd
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__adhd_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__adhd_nm", vars_mh_y_ysr__dsm__adhd))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__anx_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
Number missing
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__anx
compute_mh_y_ysr__dsm__anx_nm(
data,
name = "mh_y_ysr__dsm__anx_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__anx
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__anx
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__anx_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__anx_nm", vars_mh_y_ysr__dsm__anx))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__cond_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
Number missing
-
Summarized variables:
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__rule__cond_010
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__cond
compute_mh_y_ysr__dsm__cond_nm(
data,
name = "mh_y_ysr__dsm__cond_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__cond
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__cond
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__cond_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__cond_nm", vars_mh_y_ysr__dsm__cond))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive problems): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__dep_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): Number missing
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__tho__dep_003
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__dep
compute_mh_y_ysr__dsm__dep_nm(
data,
name = "mh_y_ysr__dsm__dep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__dep
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__dep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__dep_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__dep_nm", vars_mh_y_ysr__dsm__dep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant problems): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__opp_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): Number missing
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr__opp_005
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__opp
compute_mh_y_ysr__dsm__opp_nm(
data,
name = "mh_y_ysr__dsm__opp_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__opp
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__opp
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__opp_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__opp_nm", vars_mh_y_ysr__dsm__opp))
)
## End(Not run)
Compute "Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_y_ysr__dsm__somat_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
Number missing
-
Summarized variables:
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__dsm__somat
compute_mh_y_ysr__dsm__somat_nm(
data,
name = "mh_y_ysr__dsm__somat_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__dsm__somat
is vector of all column names
used to compute summary score of mh_y_ysr__dsm__somat
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__dsm__somat_nm(data) |>
select(
any_of(c("mh_y_ysr__dsm__somat_nm", vars_mh_y_ysr__dsm__somat))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Positive): Number missing"
Description
Computes the summary score mh_y_ysr__pos_nm
Youth Self Report [Youth] (Positive): Number missing
-
Summarized variables:
-
mh_y_ysr__pos_001
-
mh_y_ysr__pos_002
-
mh_y_ysr__pos_003
-
mh_y_ysr__pos_004
-
mh_y_ysr__pos_005
-
mh_y_ysr__pos_006
-
mh_y_ysr__pos_007
-
mh_y_ysr__pos_008
-
mh_y_ysr__pos_009
-
mh_y_ysr__pos_010
-
mh_y_ysr__pos_011
-
mh_y_ysr__pos_012
-
mh_y_ysr__pos_013
-
mh_y_ysr__pos_014
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__pos
compute_mh_y_ysr__pos_nm(
data,
name = "mh_y_ysr__pos_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__pos
is vector of all column names
used to compute summary score of mh_y_ysr__pos
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__pos_nm(data) |>
select(
any_of(c("mh_y_ysr__pos_nm", vars_mh_y_ysr__pos))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior): Number missing"
Description
Computes the summary score mh_y_ysr__synd__aggr_nm
Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior):
Number missing
-
Summarized variables:
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__aggr
compute_mh_y_ysr__synd__aggr_nm(
data,
name = "mh_y_ysr__synd__aggr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__aggr
is vector of all column names
used to compute summary score of mh_y_ysr__synd__aggr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__aggr_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__aggr_nm", vars_mh_y_ysr__synd__aggr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Number missing"
Description
Computes the summary score mh_y_ysr__synd__anxdep_nm
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Number
missing
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__anxdep
compute_mh_y_ysr__synd__anxdep_nm(
data,
name = "mh_y_ysr__synd__anxdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__anxdep
is vector of all column names
used to compute summary score of mh_y_ysr__synd__anxdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__anxdep_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__anxdep_nm", vars_mh_y_ysr__synd__anxdep))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Attention problems): Number missing"
Description
Computes the summary score mh_y_ysr__synd__attn_nm
Youth Self Report [Youth] (Syndrome Scale - Attention problems):
Number missing
-
Summarized variables:
-
mh_y_ysr__attn_001
-
mh_y_ysr__attn__adhd_001
-
mh_y_ysr__attn__adhd_002
-
mh_y_ysr__attn__adhd_003
-
mh_y_ysr__attn_002
-
mh_y_ysr__attn_003
-
mh_y_ysr__attn__adhd_004
-
mh_y_ysr__attn_004
-
mh_y_ysr__attn__adhd_005
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__attn
compute_mh_y_ysr__synd__attn_nm(
data,
name = "mh_y_ysr__synd__attn_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__attn
is vector of all column names
used to compute summary score of mh_y_ysr__synd__attn
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__attn_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__attn_nm", vars_mh_y_ysr__synd__attn))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - External): Number missing"
Description
Computes the summary score mh_y_ysr__synd__ext_nm
Youth Self Report [Youth] (Syndrome Scale - External): Number missing
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
mh_y_ysr__aggr__opp_001
-
mh_y_ysr__aggr__cond_001
-
mh_y_ysr__aggr_001
-
mh_y_ysr__aggr_002
-
mh_y_ysr__aggr__cond_002
-
mh_y_ysr__aggr__opp_002
-
mh_y_ysr__aggr__opp_003
-
mh_y_ysr__aggr__cond_003
-
mh_y_ysr__aggr__cond_004
-
mh_y_ysr__aggr_003
-
mh_y_ysr__aggr__opp_004
-
mh_y_ysr__aggr_004
-
mh_y_ysr__aggr_005
-
mh_y_ysr__aggr_006
-
mh_y_ysr__aggr__opp_005
-
mh_y_ysr__aggr__cond_005
-
mh_y_ysr__aggr__adhd_001
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__ext
compute_mh_y_ysr__synd__ext_nm(
data,
name = "mh_y_ysr__synd__ext_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__ext
is vector of all column names
used to compute summary score of mh_y_ysr__synd__ext
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__ext_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__ext_nm", vars_mh_y_ysr__synd__ext))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Internaling): Number missing"
Description
Computes the summary score mh_y_ysr__synd__int_nm
Youth Self Report [Youth] (Syndrome Scale - Internaling): Number
missing
-
Summarized variables:
-
mh_y_ysr__anxdep__dep_001
-
mh_y_ysr__anxdep__anx_001
-
mh_y_ysr__anxdep__anx_002
-
mh_y_ysr__anxdep__anx_003
-
mh_y_ysr__anxdep_001
-
mh_y_ysr__anxdep_002
-
mh_y_ysr__anxdep__dep_002
-
mh_y_ysr__anxdep__anx_004
-
mh_y_ysr__anxdep__anx_005
-
mh_y_ysr__anxdep__dep_003
-
mh_y_ysr__anxdep__anx_006
-
mh_y_ysr__anxdep__dep_004
-
mh_y_ysr__anxdep__anx_007
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__int
compute_mh_y_ysr__synd__int_nm(
data,
name = "mh_y_ysr__synd__int_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__int
is vector of all column names
used to compute summary score of mh_y_ysr__synd__int
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__int_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__int_nm", vars_mh_y_ysr__synd__int))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Other problems): Number missing"
Description
Computes the summary score mh_y_ysr__synd__othpr_nm
Youth Self Report [Youth] (Other problems): Number missing
-
Summarized variables:
-
mh_y_ysr__othpr_001
-
mh_y_ysr__othpr__dep_001
-
mh_y_ysr__othpr_002
-
mh_y_ysr__othpr_003
-
mh_y_ysr__othpr_004
-
mh_y_ysr__othpr_005
-
mh_y_ysr__othpr_006
-
mh_y_ysr__othpr__dep_002
-
mh_y_ysr__othpr__adhd_001
-
mh_y_ysr__othpr_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__othpr
compute_mh_y_ysr__synd__othpr_nm(
data,
name = "mh_y_ysr__synd__othpr_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__othpr
is vector of all column names
used to compute summary score of mh_y_ysr__synd__othpr
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__othpr_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__othpr_nm", vars_mh_y_ysr__synd__othpr))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior): Number missing"
Description
Computes the summary score mh_y_ysr__synd__rule_nm
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
Number missing
-
Summarized variables:
-
mh_y_ysr__rule_001
-
mh_y_ysr__rule__cond_001
-
mh_y_ysr__rule__cond_002
-
mh_y_ysr__rule__cond_003
-
mh_y_ysr__rule__cond_004
-
mh_y_ysr__rule_002
-
mh_y_ysr__rule__cond_005
-
mh_y_ysr__rule__cond_006
-
mh_y_ysr__rule__cond_007
-
mh_y_ysr__rule__cond_008
-
mh_y_ysr__rule__cond_009
-
mh_y_ysr__rule_003
-
mh_y_ysr__rule_004
-
mh_y_ysr__rule__cond_010
-
mh_y_ysr__rule_005
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__rule
compute_mh_y_ysr__synd__rule_nm(
data,
name = "mh_y_ysr__synd__rule_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__rule
is vector of all column names
used to compute summary score of mh_y_ysr__synd__rule
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__rule_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__rule_nm", vars_mh_y_ysr__synd__rule))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale -Social problems): Number missing"
Description
Computes the summary score mh_y_ysr__synd__soc_nm
Youth Self Report [Youth] (Syndrome Scale -Social problems): Number
missing
-
Summarized variables:
-
mh_y_ysr__soc__anx_001
-
mh_y_ysr__soc_001
-
mh_y_ysr__soc_002
-
mh_y_ysr__soc_003
-
mh_y_ysr__soc_004
-
mh_y_ysr__soc_005
-
mh_y_ysr__soc_006
-
mh_y_ysr__soc_007
-
mh_y_ysr__soc_008
-
mh_y_ysr__soc_009
-
mh_y_ysr__soc_010
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__soc
compute_mh_y_ysr__synd__soc_nm(
data,
name = "mh_y_ysr__synd__soc_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__soc
is vector of all column names
used to compute summary score of mh_y_ysr__synd__soc
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__soc_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__soc_nm", vars_mh_y_ysr__synd__soc))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Somatic complaints): Number missing"
Description
Computes the summary score mh_y_ysr__synd__som_nm
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints):
Number missing
-
Summarized variables:
-
mh_y_ysr__som__anx_001
-
mh_y_ysr__som_001
-
mh_y_ysr__som__dep_001
-
mh_y_ysr__som__somat_001
-
mh_y_ysr__som__somat_002
-
mh_y_ysr__som__somat_003
-
mh_y_ysr__som__somat_004
-
mh_y_ysr__som__somat_005
-
mh_y_ysr__som__somat_006
-
mh_y_ysr__som__somat_007
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__som
compute_mh_y_ysr__synd__som_nm(
data,
name = "mh_y_ysr__synd__som_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__som
is vector of all column names
used to compute summary score of mh_y_ysr__synd__som
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__som_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__som_nm", vars_mh_y_ysr__synd__som))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Thought problems): Number missing"
Description
Computes the summary score mh_y_ysr__synd__tho_nm
Youth Self Report [Youth] (Syndrome Scale - Thought problems): Number
missing
-
Summarized variables:
-
mh_y_ysr__tho_001
-
mh_y_ysr__tho__dep_001
-
mh_y_ysr__tho_002
-
mh_y_ysr__tho_003
-
mh_y_ysr__tho_004
-
mh_y_ysr__tho_005
-
mh_y_ysr__tho_006
-
mh_y_ysr__tho__dep_002
-
mh_y_ysr__tho_007
-
mh_y_ysr__tho_008
-
mh_y_ysr__tho_009
-
mh_y_ysr__tho__dep_003
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__tho
compute_mh_y_ysr__synd__tho_nm(
data,
name = "mh_y_ysr__synd__tho_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__tho
is vector of all column names
used to compute summary score of mh_y_ysr__synd__tho
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__tho_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__tho_nm", vars_mh_y_ysr__synd__tho))
)
## End(Not run)
Compute "Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed): Number missing"
Description
Computes the summary score mh_y_ysr__synd__wthdep_nm
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed):
Number missing
-
Summarized variables:
-
mh_y_ysr__wthdep__dep_001
-
mh_y_ysr__wthdep_001
-
mh_y_ysr__wthdep_002
-
mh_y_ysr__wthdep_003
-
mh_y_ysr__wthdep_004
-
mh_y_ysr__wthdep__dep_002
-
mh_y_ysr__wthdep__dep_003
-
mh_y_ysr__wthdep_005
-
-
Excluded values:
777
999
Usage
vars_mh_y_ysr__synd__wthdep
compute_mh_y_ysr__synd__wthdep_nm(
data,
name = "mh_y_ysr__synd__wthdep_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
Format
vars_mh_y_ysr__synd__wthdep
is vector of all column names
used to compute summary score of mh_y_ysr__synd__wthdep
scores.
Value
tbl. see combine
.
Examples
## Not run:
compute_mh_y_ysr__synd__wthdep_nm(data) |>
select(
any_of(c("mh_y_ysr__synd__wthdep_nm", vars_mh_y_ysr__synd__wthdep))
)
## End(Not run)
Compute "Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary Score): Sum"
Description
Computes the summary score nc_p_bdefs_sum
Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary
Score): Sum
-
Summarized variables:
-
nc_p_bdefs_001
-
nc_p_bdefs_002
-
nc_p_bdefs_003
-
nc_p_bdefs_004
-
nc_p_bdefs_005
-
nc_p_bdefs_006
-
nc_p_bdefs_007
-
nc_p_bdefs_008
-
nc_p_bdefs_009
-
nc_p_bdefs_010
-
nc_p_bdefs_011
-
nc_p_bdefs_012
-
nc_p_bdefs_013
-
nc_p_bdefs_014
-
nc_p_bdefs_015
-
nc_p_bdefs_016
-
nc_p_bdefs_017
-
nc_p_bdefs_018
-
nc_p_bdefs_019
-
nc_p_bdefs_020
-
Usage
vars_nc_p_bdefs
compute_nc_p_bdefs_sum(
data,
name = "nc_p_bdefs_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
Format
vars_nc_p_bdefs is a character vector of all column names
used to compute summary scores of nc_p_bdefs
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_nc_p_bdefs_sum(data) |>
select(
data,
all_of(c("nc_p_bdefs_sum", vars_nc_p_bdefs))
)
## End(Not run)
Compute "Edinburgh Handedness Inventory [Youth] (Handedness score rating)"
Description
Computes the summary score nc_y_ehis_score
Edinburgh Handedness Inventory [Youth] (Handedness score rating)
-
Summarized variables:
-
nc_y_ehis_001
-
nc_y_ehis_002
-
nc_y_ehis_003
-
nc_y_ehis_004
-
Usage
vars_nc_y_ehis
compute_nc_y_ehis_score(
data,
name = "nc_y_ehis_score",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
Format
vars_nc_y_ehis is a character vector of all column names
used to compute summary scores of nc_y_ehis
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_nc_y_ehis_score(data) |>
select(
data,
all_of(c("nc_y_ehis_score", vars_nc_y_ehis))
)
## End(Not run)
Compute "Youth Screen Time [Parent] (Problematic Media Use): Mean [Validation: No more than 1 missing or declined]"
Description
Computes the summary score nt_p_yst__pmum_mean
Youth Screen Time [Parent] (Problematic Media Use): Mean [Validation:
No more than 1 missing or declined]
-
Summarized variables:
-
nt_p_yst__pmum_001
-
nt_p_yst__pmum_002
-
nt_p_yst__pmum_003
-
nt_p_yst__pmum_004
-
nt_p_yst__pmum_005
-
nt_p_yst__pmum_006
-
nt_p_yst__pmum_007
-
nt_p_yst__pmum_008
-
nt_p_yst__pmum_009
-
-
Excluded values:
777
999
Usage
vars_nt_p_yst__pmum
compute_nt_p_yst__pmum_mean(
data,
name = "nt_p_yst__pmum_mean",
max_na = 1,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_nt_p_yst__pmum is a character vector of all column names
used to compute summary score of nt_p_yst__pmum_mean
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Youth Screen Time [Parent] (Weekday): Sum"
Description
Computes the summary score nt_p_yst__screen__wkdy_sum
Youth Screen Time [Parent] (Weekday): Sum
-
Summarized variables:
-
nt_p_yst__wkdy__hr_001
-
nt_p_yst__wkdy__min_001
-
nt_p_yst__wkdy__min_001__v01
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 item missing
Usage
vars_nt_p_yst__screen__wkdy
compute_nt_p_yst__screen__wkdy_sum(
data,
name = "nt_p_yst__screen__wkdy_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_nt_p_yst__screen__wkdy is a character vector of all column names
used to compute summary score of nt_p_yst__screen__wkdy
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Youth Screen Time [Parent] (Weekend): Sum"
Description
Computes the summary score nt_p_yst__screen__wknd_sum
Youth Screen Time [Parent] (Weekend): Sum
-
Summarized variables:
-
nt_p_yst__wknd__hr_001
-
nt_p_yst__wknd__min_001
-
nt_p_yst__wknd__min_001__v01
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 of 1 item missing
Usage
vars_nt_p_yst__screen__wknd
compute_nt_p_yst__screen__wknd_sum(
data,
name = "nt_p_yst__screen__wknd_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_nt_p_yst__screen__wknd is a character vector of all column names
used to compute summary score of nt_p_yst__screen__wknd
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Screen Time [Youth] (Weekday): Sum"
Description
Computes the summary score nt_y_stq__screen__wkdy_sum
Screen Time [Youth] (Weekday): Sum
-
Summarized variables:
-
nt_y_stq__screen__wkdy_001
-
nt_y_stq__screen__wkdy_002
-
nt_y_stq__screen__wkdy_003
-
nt_y_stq__screen__wkdy_004
-
nt_y_stq__screen__wkdy_005
-
nt_y_stq__screen__wkdy_006
-
nt_y_stq__screen__wkdy__hr_001
-
nt_y_stq__screen__wkdy__min_001
-
nt_y_stq__screen__wkdy__hr_001__v01
-
nt_y_stq__screen__wkdy__min_001__v01
-
nt_y_stq__screen__wkdy__hr_002
-
nt_y_stq__screen__wkdy__min_002
-
nt_y_stq__screen__wkdy__hr_003
-
nt_y_stq__screen__wkdy__min_003
-
nt_y_stq__screen__wkdy__hr_004
-
nt_y_stq__screen__wkdy__min_004
-
nt_y_stq__screen__wkdy__hr_005
-
nt_y_stq__screen__wkdy__min_005
-
nt_y_stq__screen__wkdy__hr_006
-
nt_y_stq__screen__wkdy__min_006
-
nt_y_stq__screen__wkdy__hr_007
-
nt_y_stq__screen__wkdy__min_007
-
nt_y_stq__screen__wkdy__hr_008
-
nt_y_stq__screen__wkdy__min_008
-
nt_y_stq__screen__wkdy__hr_009
-
nt_y_stq__screen__wkdy__min_009
-
-
Excluded values:
777
999
-
Validation criterion: none missing
Usage
vars_nt_y_stq__screen__wkdy
compute_nt_y_stq__screen__wkdy_sum(
data,
name = "nt_y_stq__screen__wkdy_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_nt_y_stq__screen__wkdy is a character vector of all column names
used to compute summary score of nt_y_stq__screen__wkdy
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Screen Time [Youth] (Weekend): Sum"
Description
Computes the summary score nt_y_stq__screen__wknd_sum
Screen Time [Youth] (Weekend): Sum
-
Summarized variables:
-
nt_y_stq__screen__wknd_001
-
nt_y_stq__screen__wknd_002
-
nt_y_stq__screen__wknd_003
-
nt_y_stq__screen__wknd_004
-
nt_y_stq__screen__wknd_005
-
nt_y_stq__screen__wknd_006
-
nt_y_stq__screen__wknd__hr_001
-
nt_y_stq__screen__wknd__min_001
-
nt_y_stq__screen__wknd__hr_001__v01
-
nt_y_stq__screen__wknd__min_001__v01
-
nt_y_stq__screen__wknd__hr_002
-
nt_y_stq__screen__wknd__min_002
-
nt_y_stq__screen__wknd__hr_003
-
nt_y_stq__screen__wknd__min_003
-
nt_y_stq__screen__wknd__hr_004
-
nt_y_stq__screen__wknd__min_004
-
nt_y_stq__screen__wknd__hr_005
-
nt_y_stq__screen__wknd__min_005
-
nt_y_stq__screen__wknd__hr_006
-
nt_y_stq__screen__wknd__min_006
-
nt_y_stq__screen__wknd__hr_007
-
nt_y_stq__screen__wknd__min_007
-
nt_y_stq__screen__wknd__hr_008
-
nt_y_stq__screen__wknd__min_008
-
nt_y_stq__screen__wknd__hr_009
-
nt_y_stq__screen__wknd__min_009
-
-
Excluded values:
777
999
-
Validation criterion: none missing
Usage
vars_nt_y_stq__screen__wknd
compute_nt_y_stq__screen__wknd_sum(
data,
name = "nt_y_stq__screen__wknd_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_nt_y_stq__screen__wknd is a character vector of all column names
used to compute summary score of nt_y_stq__screen__wknd
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_cna_sum
Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_p_cna_001
-
ph_p_cna_002
-
ph_p_cna_003
-
ph_p_cna_004
-
ph_p_cna_005
-
ph_p_cna_006
-
ph_p_cna_007
-
ph_p_cna_008
-
ph_p_cna_009
-
ph_p_cna_010
-
ph_p_cna_011
-
ph_p_cna_012
-
ph_p_cna_013
-
ph_p_cna_014
-
-
Excluded values:
999
777
-
Validation criterion: maximally 0 of 14 items missing
Usage
vars_ph_p_cna
compute_ph_p_cna_sum(
data,
name = "ph_p_cna_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
vars_ph_p_cna is a character vector of all column names
used to compute summary scores of ph_p_cna
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_p_cna_sum(data) |>
select(
all_of(c("ph_p_cna_sum", vars_ph_p_cna))
)
## End(Not run)
Compute "Developmental History [Parent]: Youth birth weight"
Description
Computes the summary score ph_p_dhx_birthweight
Developmental History [Parent]: Youth birth weight
-
Summarized variables:
-
ph_p_dhx_002__01
-
ph_p_dhx_002__02
-
-
Excluded values:
999
any value less than 0
-
Notes:
Computed using only baseline (
ses-00A
) and four-year (ses-04A
) dataThe following transformations were made prior to computing the score:
if
ph_p_dhx_002__01
< 2, set it to 2if
ph_p_dhx_002__01
> 15, set it to 15if
ph_p_dhx_002__02
> 15 / 16, set it to 15 / 16
The following decisions were made based on discordance between baseline and four-year data:
if discordance is <= 1, take baseline weight
if discordance is > 1 and baseline weight is > 4, take baseline weight
else if discordance is > 1, take four-year weight
else if baseline weight is missing, take four-year weight
else, take baseline weight
Usage
vars_ph_p_dhx_birthweight
compute_ph_p_dhx_birthweight(
data,
name = "ph_p_dhx_birthweight",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. NOTE: Only baseline and year 4 data has been used for this summary score. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_p_dhx_birthweight is a character vector of all column names
used to compute summary score of ph_p_dhx_birthweight
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Number of missing gating items"
Description
Computes the summary score ph_p_otbi_nm
Ohio State Traumatic Brain Injury Screen [Parent]: Number of missing
gating items
-
Excluded values:
777
999
Usage
vars_ph_p_otbi
compute_ph_p_otbi_nm(
data,
name = "ph_p_otbi_nm",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi is a character vector of
all column names used to compute summary score of ph_p_otbi_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness - Over 30 minutes): Count"
Description
Computes the summary score ph_p_otbi__loc__30m_count
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness - Over 30 minutes): Count
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi__loc_001
-
ph_p_otbi_002
-
ph_p_otbi__loc_002
-
ph_p_otbi_003
-
ph_p_otbi__loc_003
-
ph_p_otbi_004
-
ph_p_otbi__loc_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__03
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi_001__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__03__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__loc__30m_count
compute_ph_p_otbi__loc__30m_count(
data,
name = "ph_p_otbi__loc__30m_count",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__loc__30m_count is a character vector of all column
names used to compute summary score of ph_p_otbi__loc__30m_count
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness): LOC before the age of 15"
Description
Computes the summary score ph_p_otbi__loc_before15
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): LOC before the age of 15
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi__loc_001
-
ph_p_otbi__age_001
-
ph_p_otbi_002
-
ph_p_otbi__loc_002
-
ph_p_otbi__age_002
-
ph_p_otbi_003
-
ph_p_otbi__loc_003
-
ph_p_otbi__age_003
-
ph_p_otbi_004
-
ph_p_otbi__loc_004
-
ph_p_otbi__age_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_005
-
ph_p_otbi__age_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__04
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt__age_001a
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt__age_002a
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi__rpt__age_003a
-
ph_p_otbi_001__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__age_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__age_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__age_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__age_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__age_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__04__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
ph_p_otbi__rpt__age_001a__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__loc_before15
compute_ph_p_otbi__loc_before15(
data,
name = "ph_p_otbi__loc_before15",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
Format
vars_ph_p_otbi__loc_before15 is a character vector of all column
names used to compute summary score of ph_p_otbi__loc_before15
.
Value
tbl. The input data frame with the summary score appended as a new column.
See Also
compute_ph_p_otbi__loc_tbiage()
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness): Count"
Description
Computes the summary score ph_p_otbi__loc_count
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Count
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi__loc_001
-
ph_p_otbi_002
-
ph_p_otbi__loc_002
-
ph_p_otbi_003
-
ph_p_otbi__loc_003
-
ph_p_otbi_004
-
ph_p_otbi__loc_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__01
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi_001__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__01__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__loc_count
compute_ph_p_otbi__loc_count(
data,
name = "ph_p_otbi__loc_count",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__loc_count is a character vector of all column names
used to compute summary score of ph_p_otbi__loc_count
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Loss of consciousness): Age of first injury with LOC"
Description
Computes the summary score ph_p_otbi__loc_tbiage
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Age of first injury with LOC
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi__loc_001
-
ph_p_otbi__age_001
-
ph_p_otbi_002
-
ph_p_otbi__loc_002
-
ph_p_otbi__age_002
-
ph_p_otbi_003
-
ph_p_otbi__loc_003
-
ph_p_otbi__age_003
-
ph_p_otbi_004
-
ph_p_otbi__loc_004
-
ph_p_otbi__age_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_005
-
ph_p_otbi__age_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__04
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt__age_001a
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt__age_002a
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi__rpt__age_003a
-
ph_p_otbi_001__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__age_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__age_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__age_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__age_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__age_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__04__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
ph_p_otbi__rpt__age_001a__l
-
-
Excluded values:
777
999
any reported age less than or equal to 0
-
Notes:
The output is set to
NA
for the following cases:minimum age is less than 0
minimum age is higher than age at visit
no head or neck injury/impact is reported
Usage
vars_ph_p_otbi__loc_tbiage
compute_ph_p_otbi__loc_tbiage(
data,
name = "ph_p_otbi__loc_tbiage",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__loc_tbiage is a character vector of all column names
used to compute summary score of ph_p_otbi__loc_tbiage
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries): Count"
Description
Computes the summary score ph_p_otbi__rpt_count
Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries):
Count [Validation: No more than 2 missing or declined at baseline
and no more than 0 missing or declined at non-baseline events]
-
Summarized variables:
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt_001__l
-
-
Excluded values:
777
999
-
Validation criterion:
maximally 2 item missing at baseline event
maximally 0 item missing at non-baseline events
Usage
vars_ph_p_otbi__rpt_count
compute_ph_p_otbi__rpt_count(
data,
name = "ph_p_otbi__rpt_count",
exclude = c("777", "999"),
combine = TRUE,
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 2). |
Format
vars_ph_p_otbi__rpt_count is a character vector of all column names
used to compute summary score of ph_p_otbi__rpt_count
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: No head or neck injury/impact"
Description
Computes the summary score ph_p_otbi__tbi1a
Ohio State Traumatic Brain Injury Screen [Parent]: No head or neck
injury/impact
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__rpt_001
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__rpt_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__tbi1a
compute_ph_p_otbi__tbi1a(
data,
name = "ph_p_otbi__tbi1a",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__tbi1a is a character vector of all column names
used to compute summary score of ph_p_otbi__tbi1a
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Improbable TBI"
Description
Computes the summary score ph_p_otbi__tbi1b
Ohio State Traumatic Brain Injury Screen [Parent]: Improbable TBI
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__daz_001
-
ph_p_otbi__daz_002
-
ph_p_otbi__daz_003
-
ph_p_otbi__daz_004
-
ph_p_otbi__daz_005
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt__daz_001
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__daz_001__l
-
ph_p_otbi__daz_002__l
-
ph_p_otbi__daz_003__l
-
ph_p_otbi__daz_004__l
-
ph_p_otbi__daz_005__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
ph_p_otbi__rpt__daz_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__tbi1b
compute_ph_p_otbi__tbi1b(
data,
name = "ph_p_otbi__tbi1b",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__tbi1b is a character vector of all column names
used to compute summary score of ph_p_otbi__tbi1b
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Possible mild TBI"
Description
Computes the summary score ph_p_otbi__tbi2
Ohio State Traumatic Brain Injury Screen [Parent]: Possible mild TBI
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__daz_001
-
ph_p_otbi__daz_002
-
ph_p_otbi__daz_003
-
ph_p_otbi__daz_004
-
ph_p_otbi__daz_005
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt__daz_001
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__daz_001__l
-
ph_p_otbi__daz_002__l
-
ph_p_otbi__daz_003__l
-
ph_p_otbi__daz_004__l
-
ph_p_otbi__daz_005__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
ph_p_otbi__rpt__daz_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__tbi2
compute_ph_p_otbi__tbi2(
data,
name = "ph_p_otbi__tbi2",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__tbi2 is a character vector of all column names
used to compute summary score of ph_p_otbi__tbi2
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Mild TBI"
Description
Computes the summary score ph_p_otbi__tbi3
Ohio State Traumatic Brain Injury Screen [Parent]: Mild TBI
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__loc__add_001__02
-
ph_p_otbi__loc__add_001__03
-
ph_p_otbi__rpt_001
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__loc__add_001__02__l
-
ph_p_otbi__loc__add_001__03__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__rpt__loc_001__l
-
-
Excluded values:
777
999
Usage
vars_ph_p_otbi__tbi3
compute_ph_p_otbi__tbi3(
data,
name = "ph_p_otbi__tbi3",
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
Format
vars_ph_p_otbi__tbi3 is a character vector of all column names
used to compute summary score of ph_p_otbi__tbi3
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Ohio State Traumatic Brain Injury Screen [Parent]: Worst injury overall"
Description
Computes the summary score ph_p_otbi_tbiworst
Ohio State Traumatic Brain Injury Screen [Parent]: Worst injury overall
-
Summarized variables:
-
ph_p_otbi_001
-
ph_p_otbi_002
-
ph_p_otbi_003
-
ph_p_otbi_004
-
ph_p_otbi_005
-
ph_p_otbi__loc__add_001
-
ph_p_otbi__rpt_001
-
ph_p_otbi_001__l
-
ph_p_otbi_002__l
-
ph_p_otbi_003__l
-
ph_p_otbi_004__l
-
ph_p_otbi_005__l
-
ph_p_otbi__loc__add_001__l
-
ph_p_otbi__rpt_001__l
-
ph_p_otbi__loc_001
-
ph_p_otbi__loc_002
-
ph_p_otbi__loc_003
-
ph_p_otbi__loc_004
-
ph_p_otbi__loc_005
-
ph_p_otbi__daz_001
-
ph_p_otbi__daz_002
-
ph_p_otbi__daz_003
-
ph_p_otbi__daz_004
-
ph_p_otbi__daz_005
-
ph_p_otbi__rpt__loc_001
-
ph_p_otbi__rpt__daz_001
-
ph_p_otbi__rpt_002
-
ph_p_otbi__rpt__loc__daz_002
-
ph_p_otbi__rpt_003
-
ph_p_otbi__rpt__loc__daz_003
-
ph_p_otbi__loc_001__l
-
ph_p_otbi__loc_002__l
-
ph_p_otbi__loc_003__l
-
ph_p_otbi__loc_004__l
-
ph_p_otbi__loc_005__l
-
ph_p_otbi__daz_001__l
-
ph_p_otbi__daz_002__l
-
ph_p_otbi__daz_003__l
-
ph_p_otbi__daz_004__l
-
ph_p_otbi__daz_005__l
-
ph_p_otbi__rpt__loc_001__l
-
ph_p_otbi__rpt__daz_001__l
-
ph_p_otbi__loc__add_001__02
-
ph_p_otbi__loc__add_001__03
-
ph_p_otbi__loc__add_001__02__l
-
ph_p_otbi__loc__add_001__03__l
-
-
Excluded values:
777
999
-
Notes:
Computed using the following summary scores:
ph_p_otbi__tbi1a
ph_p_otbi__tbi1b
ph_p_otbi__tbi2
ph_p_otbi__tbi3
ph_p_otbi__tbi4
ph_p_otbi__tbi5
Usage
vars_ph_p_otbi_tbiworst
compute_ph_p_otbi_tbiworst(
data,
name = "ph_p_otbi_tbiworst",
keep_summaries = FALSE,
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
keep_summaries |
logical. If |
combine |
logical. If |
Format
vars_ph_p_otbi_tbiworst is a character vector of all column names
used to compute summary score of ph_p_otbi_tbiworst
.
Value
tbl. The input data frame with the summary score(s) appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Female): Mean"
Description
Computes the summary score ph_p_pds__f_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Mean [Validation: No more than 1 missing or declined]
-
Summarized variables:
-
ph_p_pds_001
-
ph_p_pds_002
-
ph_p_pds_003
-
ph_p_pds__f_001
-
ph_p_pds__f_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 item missing
-
Notes:
Values in
ph_p_pds__f_002
were recoded:"0" –> "1",
"1" –> "4"
Usage
vars_ph_p_pds__f
compute_ph_p_pds__f_mean(
data,
name = "ph_p_pds__f_mean",
exclude = c("777", "999"),
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_p_pds__f is a character vector of all column names
used to compute summary score of ph_p_pds__f_mean
and
ph_p_pds__f_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Female): Approximate tanner stages"
Description
Computes the summary score ph_p_pds__f_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Approximate tanner stages [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_p_pds_002
-
ph_p_pds__f_001
-
ph_p_pds__f_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_pds__f_categ
compute_ph_p_pds__f_categ(
data,
name = "ph_p_pds__f_categ",
exclude = c("777", "999"),
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_p_pds__f is a character vector of all column names
used to compute summary score of ph_p_pds__f_categ
and
ph_p_pds__f__categ_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Male): Mean"
Description
Computes the summary score ph_p_pds__m_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Mean [Validation: No more than 1 missing or declined]
-
Summarized variables:
-
ph_p_pds_001
-
ph_p_pds_002
-
ph_p_pds_003
-
ph_p_pds__m_001
-
ph_p_pds__m_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 item missing
Usage
vars_ph_p_pds__m
compute_ph_p_pds__m_mean(
data,
name = "ph_p_pds__m_mean",
exclude = c("777", "999"),
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_p_pds__m is a character vector of all column names
used to compute summary score of ph_p_pds__m_mean
and
ph_p_pds__m_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Parent] (Male): Approximate tanner stages"
Description
Computes the summary score ph_p_pds__m_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Approximate tanner stages [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_p_pds_002
-
ph_p_pds__m_001
-
ph_p_pds__m_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_pds__m_categ
compute_ph_p_pds__m_categ(
data,
name = "ph_p_pds__m_categ",
exclude = c("777", "999"),
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_p_pds__m is a character vector of all column names
used to compute summary score of ph_p_pds__m_categ
and
ph_p_pds__m__categ_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Sleep Disturbance Scale [Parent] (Disorder of arousal): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__da_sum
Sleep Disturbance Scale [Parent] (Disorder of arousal): Sum
[Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__da_001
-
ph_p_sds__da_002
-
ph_p_sds__da_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__da
compute_ph_p_sds__da_sum(
data,
name = "ph_p_sds__da_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__da_sum
and ph_p_sds__da_nm
.
Examples
## Not run:
compute_ph_p_sds__da_sum(data) |>
select(
all_of(c("ph_p_sds__da_sum", vars_ph_p_sds__da))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining sleep): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__dims_sum
Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining
sleep): Sum [Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__dims_001
-
ph_p_sds__dims_002
-
ph_p_sds__dims_003
-
ph_p_sds__dims_004
-
ph_p_sds__dims_005
-
ph_p_sds__dims_006
-
ph_p_sds__dims_007
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__dims
compute_ph_p_sds__dims_sum(
data,
name = "ph_p_sds__dims_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__dims_sum
and ph_p_sds__dims_nm
.
Examples
## Not run:
compute_ph_p_sds__dims_sum(data) |>
select(
all_of(c("ph_p_sds__dims_sum", vars_ph_p_sds__dims))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__does_sum
Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence): Sum
[Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__does_001
-
ph_p_sds__does_002
-
ph_p_sds__does_003
-
ph_p_sds__does_004
-
ph_p_sds__does_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__does
compute_ph_p_sds__does_sum(
data,
name = "ph_p_sds__does_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__does_sum
and ph_p_sds__does_nm
.
Examples
## Not run:
compute_ph_p_sds__does_sum(data) |>
select(
all_of(c("ph_p_sds__does_sum", vars_ph_p_sds__does))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__hyphy_sum
Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis): Sum
[Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__hyphy_001
-
ph_p_sds__hyphy_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__hyphy
compute_ph_p_sds__hyphy_sum(
data,
name = "ph_p_sds__hyphy_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__hyphy_sum
and ph_p_sds__hyphy_nm
.
Examples
## Not run:
compute_ph_p_sds__hyphy_sum(data) |>
select(
all_of(c("ph_p_sds__hyphy_sum", vars_ph_p_sds__hyphy))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Sleep breathing disorders): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__sbd_sum
Sleep Disturbance Scale [Parent] (Sleep breathing disorders): Sum
[Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__sbd_001
-
ph_p_sds__sbd_002
-
ph_p_sds__sbd_003
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__sbd
compute_ph_p_sds__sbd_sum(
data,
name = "ph_p_sds__sbd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__sbd_sum
and ph_p_sds__sbd_nm
.
Examples
## Not run:
compute_ph_p_sds__sbd_sum(data) |>
select(
all_of(c("ph_p_sds__sbd_sum", vars_ph_p_sds__sbd))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds__swtd_sum
Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders): Sum
[Validation: No more than 0 missing or declined]
-
Summarized variables:
-
ph_p_sds__swtd_001
-
ph_p_sds__swtd_002
-
ph_p_sds__swtd_003
-
ph_p_sds__swtd_004
-
ph_p_sds__swtd_005
-
ph_p_sds__swtd_006
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds__swtd
compute_ph_p_sds__swtd_sum(
data,
name = "ph_p_sds__swtd_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds__swtd_sum
and ph_p_sds__swtd_nm
.
Examples
## Not run:
compute_ph_p_sds__swtd_sum(data) |>
select(
all_of(c("ph_p_sds__swtd_sum", vars_ph_p_sds__swtd))
)
## End(Not run)
Compute "Sleep Disturbance Scale [Parent] (Total): Sum [Validation: No more than 0 missing or declined]"
Description
Computes the summary score ph_p_sds_sum
Sleep Disturbance Scale [Parent] (Total): Sum [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_p_sds__dims_001
-
ph_p_sds__dims_002
-
ph_p_sds__dims_003
-
ph_p_sds__dims_004
-
ph_p_sds__dims_005
-
ph_p_sds__swtd_001
-
ph_p_sds__swtd_002
-
ph_p_sds__swtd_003
-
ph_p_sds__hyphy_001
-
ph_p_sds__dims_006
-
ph_p_sds__dims_007
-
ph_p_sds__swtd_004
-
ph_p_sds__sbd_001
-
ph_p_sds__sbd_002
-
ph_p_sds__sbd_003
-
ph_p_sds__hyphy_002
-
ph_p_sds__da_001
-
ph_p_sds__swtd_005
-
ph_p_sds__swtd_006
-
ph_p_sds__da_002
-
ph_p_sds__da_003
-
ph_p_sds__does_001
-
ph_p_sds__does_002
-
ph_p_sds__does_003
-
ph_p_sds__does_004
-
ph_p_sds__does_005
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_p_sds_sum
compute_ph_p_sds_sum(
data,
name = "ph_p_sds_sum",
max_na = 0,
exclude = c("777", "999"),
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
Format
character vector of all column names
used to compute summary scores of ph_p_sds_sum
and ph_p_sds_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_p_sds_sum(data) |>
select(
all_of(c("ph_p_sds_sum", vars_ph_p_sds_sum))
)
## End(Not run)
Compute "Anthropometrics [Youth] (Height): Mean"
Description
Computes the summary score ph_y_anthr__height_mean
Anthropometrics [Youth] (Height): Mean
-
Summarized variables:
-
ph_y_anthr__height__r01_001
-
ph_y_anthr__height__r02_001
-
ph_y_anthr__height__r03_001
-
-
Excluded values: none
Calculation
There are at most 3 possible measurements, and the calculation is as follows:
0 missing, find the max and min of the three, and take the average of the min and max. Then compare the average to the third value.
third value < average -> mean(min, third value)
third value > average -> mean(max, third value)
third value = average -> third value
1 missing, mean of the rest two
2 missing, use the last one
3 missing, NA
Usage
vars_ph_y_anthr__height
compute_ph_y_anthr__height_mean(
data,
name = "ph_y_anthr__height_mean",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_y_anthr__height is a character vector of all column names
used to compute summary scores of ph_y_anthr__height
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_anthr__height_mean(data) |>
select(
all_of(c("ph_y_anthr__height_mean", vars_ph_y_anthr__height))
)
## End(Not run)
Compute "Anthropometrics [Youth] (Weight): Mean"
Description
Computes the summary score ph_y_anthr__weight_mean
Anthropometrics [Youth] (Weight): Mean
-
Summarized variables: *
ph_y_anthr__weight__r01_001
-
ph_y_anthr__weight__r02_001
-
ph_y_anthr__weight__r03_001
-
-
Excluded values: none
Calculation
There are at most 3 possible measurements, and the calculation is as follows:
0 missing, find the max and min of the three, and take the average of the min and max. Then compare the average to the third value.
third value < average -> mean(min, third value)
third value > average -> mean(max, third value)
third value = average -> third value
1 missing, mean of the rest two
2 missing, use the last one
3 missing, NA
Usage
vars_ph_y_anthr__weight
compute_ph_y_anthr__weight_mean(
data,
name = "ph_y_anthr__weight_mean",
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_y_anthr__weight is a character vector of all column names
used to compute summary scores of ph_y_anthr__weight
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_anthr__weight_mean(data) |>
select(
all_of(c("ph_y_anthr__weight_mean", vars_ph_y_anthr__weight))
)
## End(Not run)
Compute "Blood Pressure [Youth] (Diastolic): Mean"
Description
Computes the summary score ph_y_bp__dia_mean
Blood Pressure [Youth] (Diastolic): Mean
-
Summarized variables:
-
ph_y_bp__dia__r01_001
-
ph_y_bp__dia__r01_002
-
ph_y_bp__dia__r01_003
-
ph_y_bp__dia__r02_001
-
ph_y_bp__dia__r02_002
-
ph_y_bp__dia__r03_001
-
ph_y_bp__dia__r03_002
-
-
Excluded values: none
Usage
vars_ph_y_bp__dia
compute_ph_y_bp__dia_mean(data, name = "ph_y_bp__dia_mean", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_y_bp__dia is a character vector of all column names
used to compute summary scores of ph_y_bp__dia
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_bp__dia_mean(data) |>
select(
all_of(c("ph_y_bp__dia_mean", vars_ph_y_bp__dia))
)
## End(Not run)
Compute "Blood Pressure [Youth] (Heart rate): Mean"
Description
Computes the summary score ph_y_bp__hrate_mean
Blood Pressure [Youth] (Heart rate): Mean
-
Summarized variables:
-
ph_y_bp__hrate__r01_001
-
ph_y_bp__hrate__r01_002
-
ph_y_bp__hrate__r01_003
-
ph_y_bp__hrate__r02_001
-
ph_y_bp__hrate__r02_002
-
ph_y_bp__hrate__r03_001
-
ph_y_bp__hrate__r03_002
-
-
Excluded values: none
Usage
vars_ph_y_bp__hrate
compute_ph_y_bp__hrate_mean(data, name = "ph_y_bp__hrate_mean", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_y_bp__hrate is a character vector of all column names
used to compute summary scores of ph_y_bp__hrate
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_bp__hrate_mean(data) |>
select(
all_of(c("ph_y_bp__hrate_mean", vars_ph_y_bp__hrate))
)
## End(Not run)
Compute "Blood Pressure [Youth] (Systolic): Mean"
Description
Computes the summary score ph_y_bp__sys_mean
Blood Pressure [Youth] (Systolic): Mean
-
Summarized variables:
-
ph_y_bp__sys__r01_001
-
ph_y_bp__sys__r01_002
-
ph_y_bp__sys__r01_003
-
ph_y_bp__sys__r02_001
-
ph_y_bp__sys__r02_002
-
ph_y_bp__sys__r03_001
-
ph_y_bp__sys__r03_002
-
-
Excluded values: none
Usage
vars_ph_y_bp__sys
compute_ph_y_bp__sys_mean(data, name = "ph_y_bp__sys_mean", combine = TRUE)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
Format
vars_ph_y_bp__sys is a character vector of all column names
used to compute summary scores of ph_y_bp__sys
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_ph_y_bp__sys_mean(data) |>
select(
all_of(c("ph_y_bp__sys_mean", vars_ph_y_bp__sys))
)
## End(Not run)
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Female): Mean"
Description
Computes the summary score ph_y_pds__f_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Mean [Validation: No more than 1 missing or declined]
-
Summarized variables:
-
ph_y_pds_001
-
ph_y_pds_002
-
ph_y_pds_003
-
ph_y_pds__f_001
-
ph_y_pds__f_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 item missing
Usage
vars_ph_y_pds__f
compute_ph_y_pds__f_mean(
data,
name = "ph_y_pds__f_mean",
exclude = c("777", "999"),
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_y_pds__f is a character vector of all column names
used to compute summary score of ph_y_pds__f_mean
and
ph_y_pds__f_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Female): Approximate tanner stages"
Description
Computes the summary score ph_y_pds__f_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Approximate tanner stages [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_y_pds_002
-
ph_y_pds__f_001
-
ph_y_pds__f_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_y_pds__f_categ
compute_ph_y_pds__f_categ(
data,
name = "ph_y_pds__f_categ",
exclude = c("777", "999"),
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_y_pds__f is a character vector of all column names
used to compute summary score of ph_y_pds__f_categ
and
ph_y_pds__f__categ_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Male): Mean"
Description
Computes the summary score ph_y_pds__m_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Mean [Validation: No more than 1 missing or declined]
-
Summarized variables:
-
ph_y_pds_001
-
ph_y_pds_002
-
ph_y_pds_003
-
ph_y_pds__m_001
-
ph_y_pds__m_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 1 item missing
Usage
vars_ph_y_pds__m
compute_ph_y_pds__m_mean(
data,
name = "ph_y_pds__m_mean",
combine = TRUE,
exclude = c("777", "999"),
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_y_pds__m is a character vector of all column names
used to compute summary score of ph_y_pds__m_mean
and
ph_y_pds__m_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Pubertal Development Scale & Menstrual Cycle Survey History [Youth] (Male): Approximate tanner stages"
Description
Computes the summary score ph_y_pds__m_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Approximate tanner stages [Validation: No more than 0
missing or declined]
-
Summarized variables:
-
ph_y_pds_002
-
ph_y_pds__m_001
-
ph_y_pds__m_002
-
-
Excluded values:
777
999
-
Validation criterion: maximally 0 items missing
Usage
vars_ph_y_pds__m_categ
compute_ph_y_pds__m_categ(
data,
name = "ph_y_pds__m_categ",
combine = TRUE,
exclude = c("777", "999"),
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
Format
vars_ph_y_pds__m is a character vector of all column names
used to compute summary score of ph_y_pds__m_categ
and
ph_y_pds__m__categ_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative expectancies): Prorated sum"
Description
Computes the summary score su_y_alcexp__neg_prsum
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative
expectancies): Prorated sum
-
Summarized variables:
-
su_y_alcexp__neg_001
-
su_y_alcexp__neg_002
-
su_y_alcexp__neg_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 3 items missing
Usage
vars_su_y_alcexp__neg
compute_su_y_alcexp__neg_prsum(
data,
name = "su_y_alcexp__neg_prsum",
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_alcexp__neg is a character vector of all column names
used to compute summary score of su_y_alcexp__neg_prsum
and
su_y_alcexp__neg_nm
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive expectancies): Prorated sum"
Description
Computes the summary score su_y_alcexp__pos_prsum
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive
expectancies): Prorated sum
-
Summarized variables:
-
su_y_alcexp__pos_001
-
su_y_alcexp__pos_002
-
su_y_alcexp__pos_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 3 items missing
Usage
vars_su_y_alcexp__pos
compute_su_y_alcexp__pos_prsum(
data,
name = "su_y_alcexp__pos_prsum",
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_alcexp__pos is a character vector of all column names
used to compute summary score of su_y_alcexp__pos_prsum
and
su_y_alcexp__pos_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Hangover Symptoms Scale (HSS) [Youth]: Sum"
Description
Computes the summary score su_y_alchss_sum
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Sum
-
Summarized variables:
-
su_y_alchss_001
-
su_y_alchss_002
-
su_y_alchss_003
-
su_y_alchss_004
-
su_y_alchss_005
-
su_y_alchss_006
-
su_y_alchss_007
-
su_y_alchss_008
-
su_y_alchss_009
-
su_y_alchss_010
-
su_y_alchss_011
-
su_y_alchss_012
-
su_y_alchss_013
-
su_y_alchss_014
-
su_y_alchss_001__l
-
su_y_alchss_002__l
-
su_y_alchss_003__l
-
su_y_alchss_004__l
-
su_y_alchss_005__l
-
su_y_alchss_006__l
-
su_y_alchss_007__l
-
su_y_alchss_008__l
-
su_y_alchss_009__l
-
su_y_alchss_010__l
-
su_y_alchss_011__l
-
su_y_alchss_012__l
-
su_y_alchss_013__l
-
su_y_alchss_014__l
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
vars_su_y_alchss
compute_su_y_alchss_sum(
data,
name = "su_y_alchss_sum",
max_na = 0,
combine = TRUE
)
Arguments
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
Format
vars_su_y_alchss is a table of all column names
used to compute summary score of su_y_alchss
.
Value
tbl. The input data frame with the summary score appended as a new column.
Examples
## Not run:
compute_su_y_alchss_sum(data)
## End(Not run)
Compute "Alcohol Problem Index (RAPI) [Youth]: Prorated sum"
Description
Computes the summary score su_y_alcprob_prsum
Alcohol Problem Index (RAPI) [Youth]: Prorated sum [Validation: No more
than 2 missing or declined]
-
Summarized variables:
-
su_y_alcprob_001
-
su_y_alcprob_002
-
su_y_alcprob_003
-
su_y_alcprob_004
-
su_y_alcprob_005
-
su_y_alcprob_006
-
su_y_alcprob_007
-
su_y_alcprob_008
-
su_y_alcprob_009
-
su_y_alcprob_010
-
su_y_alcprob_012
-
su_y_alcprob_016
-
su_y_alcprob_017
-
su_y_alcprob_018
-
su_y_alcprob_001__l
-
su_y_alcprob_002__l
-
su_y_alcprob_003__l
-
su_y_alcprob_004__l
-
su_y_alcprob_005__l
-
su_y_alcprob_006__l
-
su_y_alcprob_007__l
-
su_y_alcprob_008__l
-
su_y_alcprob_009__l
-
su_y_alcprob_010__l
-
su_y_alcprob_012__l
-
su_y_alcprob_016__l
-
su_y_alcprob_017__l
-
su_y_alcprob_018__l
-
-
Excluded values: none
-
Validation criterion: maximally 2 items missing
Usage
vars_su_y_alcprob
compute_su_y_alcprob_prsum(
data,
name = "su_y_alcprob_prsum",
combine = TRUE,
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_alcprob is a table with pairs of baseline and longitudinal
redcap fields used to compute summary score of su_y_alcprob_prsum
and
su_y_alcprob_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (Last 6 months): Mean [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__6mo_mean
Alcohol Subject Response and Effects [Youth] (Last 6 months): Mean
[Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__6mo_001
-
su_y_alcsre__6mo_002
-
su_y_alcsre__6mo_003
-
su_y_alcsre__6mo_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
vars_su_y_alcsre__6mo
compute_su_y_alcsre__6mo_mean(
data,
name = "su_y_alcsre__6mo_mean",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_alcsre__6mo is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__6mo
(_mean
, _count
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (First 5 times ever drank): Mean [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__first5_mean
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Mean [Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__first5_001
-
su_y_alcsre__first5_002
-
su_y_alcsre__first5_003
-
su_y_alcsre__first5_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
vars_su_y_alcsre__first5
compute_su_y_alcsre__first5_mean(
data,
name = "su_y_alcsre__first5_mean",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_alcsre__first5 is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__first5
(_mean
, _count
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Alcohol Subject Response and Effects [Youth] (Heaviest drinking period): Mean [Validation: None missing or declined]"
Description
Computes the summary score su_y_alcsre__hvy_mean
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Mean [Validation: None missing or declined]
-
Summarized variables:
-
su_y_alcsre__hvy_001
-
su_y_alcsre__hvy_002
-
su_y_alcsre__hvy_003
-
su_y_alcsre__hvy_004
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 4 items missing
Usage
vars_su_y_alcsre__hvy
compute_su_y_alcsre__hvy_mean(
data,
name = "su_y_alcsre__hvy_mean",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_alcsre__hvy is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__hvy
(_mean
, _count
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Coffee): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__coffee_sum
Caffeine Use Questionnaire [Youth] (Coffee): Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__coffee_001
-
su_y_caff__coffee_001__01__01
-
su_y_caff__coffee_001__01__02
-
su_y_caff__coffee_001__01__03
-
su_y_caff__coffee_001__02__01
-
su_y_caff__coffee_001__02__02
-
su_y_caff__coffee_001__02__03
-
su_y_caff__coffee_001__03__01
-
su_y_caff__coffee_001__03__02
-
su_y_caff__coffee_001__03__03
-
su_y_caff__coffee_001__04__01
-
su_y_caff__coffee_001__04__02
-
su_y_caff__coffee_001__04__03
-
su_y_caff__coffee_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__coffee
compute_su_y_caff__coffee_sum(
data,
name = "su_y_caff__coffee_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__coffee is a character vector of all column names used
to compute compute_su_y_caff__coffee_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Energy): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__energy_sum
Caffeine Use Questionnaire [Youth] (Energy): Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__energy_001
-
su_y_caff__energy_001__l
-
su_y_caff__energy__shot_001__01
-
su_y_caff__energy__shot_001__02
-
su_y_caff__energy__drink_001__01__01
-
su_y_caff__energy__drink_001__01__02
-
su_y_caff__energy__drink_001__01__03
-
su_y_caff__energy__drink_001__02__01
-
su_y_caff__energy__drink_001__02__02
-
su_y_caff__energy__drink_001__02__03
-
su_y_caff__energy__drink_001__03__01
-
su_y_caff__energy__drink_001__03__02
-
su_y_caff__energy__drink_001__03__03
-
su_y_caff__energy__drink_001__04__01
-
su_y_caff__energy__drink_001__04__02
-
su_y_caff__energy__drink_001__04__03
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__energy
compute_su_y_caff__energy_sum(
data,
name = "su_y_caff__energy_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__energy is a character vector of all column names used
to compute compute_su_y_caff__energy_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Energy drink): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__energy__drink_sum
Caffeine Use Questionnaire [Youth] (Energy drink):
Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__energy__drink_001__01__01
-
su_y_caff__energy__drink_001__01__02
-
su_y_caff__energy__drink_001__01__03
-
su_y_caff__energy__drink_001__02__01
-
su_y_caff__energy__drink_001__02__02
-
su_y_caff__energy__drink_001__02__03
-
su_y_caff__energy__drink_001__03__01
-
su_y_caff__energy__drink_001__03__02
-
su_y_caff__energy__drink_001__03__03
-
su_y_caff__energy__drink_001__04__01
-
su_y_caff__energy__drink_001__04__02
-
su_y_caff__energy__drink_001__04__03
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__energy__drink
compute_su_y_caff__energy__drink_sum(
data,
name = "su_y_caff__energy__drink_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__energy__drink is a character vector
of all column names used to compute compute_su_y_caff__energy__drink_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Energy shot): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__energy__shot_sum
Caffeine Use Questionnaire [Youth] (Energy shot): Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__energy__shot_001__01
-
su_y_caff__energy__shot_001__02
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__energy__shot
compute_su_y_caff__energy__shot_sum(
data,
name = "su_y_caff__energy__shot_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__energy__shot is a character vector of all column
names used to compute compute_su_y_caff__energy__shot_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Espresso): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__espres_sum
Caffeine Use Questionnaire [Youth] (Espresso): Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__espres_001
-
su_y_caff__espres_001__01
-
su_y_caff__espres_001__02
-
su_y_caff__espres_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__espres
compute_su_y_caff__espres_sum(
data,
name = "su_y_caff__espres_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__espres is a character vector of all column names used
to compute compute_su_y_caff__espres_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Other): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__oth_sum
Caffeine Use Questionnaire [Youth] (Other): Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__oth_001__01
-
su_y_caff__oth_001__02
-
su_y_caff__oth_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__oth
compute_su_y_caff__oth_sum(data, name = "su_y_caff__oth_sum", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__oth is a character vector of all column names used
to compute compute_su_y_caff__oth_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Soda): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__soda_sum
Caffeine Use Questionnaire [Youth] (Soda) : Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__soda_001
-
su_y_caff__soda_001__01__01
-
su_y_caff__soda_001__01__02
-
su_y_caff__soda_001__01__03
-
su_y_caff__soda_001__02__01
-
su_y_caff__soda_001__02__02
-
su_y_caff__soda_001__02__03
-
su_y_caff__soda_001__03__01
-
su_y_caff__soda_001__03__02
-
su_y_caff__soda_001__03__03
-
su_y_caff__soda_001__04__01
-
su_y_caff__soda_001__04__02
-
su_y_caff__soda_001__04__03
-
su_y_caff__soda_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__soda
compute_su_y_caff__soda_sum(data, name = "su_y_caff__soda_sum", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__soda is a character vector of all column names used
to compute compute_su_y_caff__soda_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Caffeine supplements): Sum [Validation: None]"
Description
Computes the summary score su_y_caff__suppl_sum
Caffeine Use Questionnaire [Youth] (Caffeine supplements):
Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__suppl_001__01__01
-
su_y_caff__suppl_001__01__02
-
su_y_caff__suppl_001__02__01
-
su_y_caff__suppl_001__02__02
-
su_y_caff__suppl_001__03__01
-
su_y_caff__suppl_001__03__02
-
su_y_caff__suppl_001__04__01
-
su_y_caff__suppl_001__04__02
-
su_y_caff__suppl_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__suppl
compute_su_y_caff__suppl_sum(
data,
name = "su_y_caff__suppl_sum",
combine = TRUE
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__suppl is a character vector of all column names used
to compute compute_su_y_caff__suppl_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Caffeine Use Questionnaire [Youth] (Tea) : Sum [Validation: None]"
Description
Computes the summary score su_y_caff__tea_sum
Caffeine Use Questionnaire [Youth] (Tea) : Sum [Validation: None]
-
Summarized variables:
-
su_y_caff__tea_001
-
su_y_caff__tea_001__01__01
-
su_y_caff__tea_001__01__02
-
su_y_caff__tea_001__01__03
-
su_y_caff__tea_001__02__01
-
su_y_caff__tea_001__02__02
-
su_y_caff__tea_001__02__03
-
su_y_caff__tea_001__03__01
-
su_y_caff__tea_001__03__02
-
su_y_caff__tea_001__03__03
-
su_y_caff__tea_001__04__01
-
su_y_caff__tea_001__04__02
-
su_y_caff__tea_001__04__03
-
su_y_caff__tea_001__l
-
-
Excluded values: none
-
Validation criterion: none
Usage
vars_su_y_caff__tea
compute_su_y_caff__tea_sum(data, name = "su_y_caff__tea_sum", combine = TRUE)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
Format
vars_su_y_caff__tea is a character vector of all column names used
to compute compute_su_y_caff__tea_sum
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of negative expectancies): Prorated sum"
Description
Computes the summary score su_y_cigexp__neg_prsum
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Prorated sum [Validation: No more than 0
missing or declined]
Note: all 0s are changed to NAs prior to calculating pro-rated sum
-
Summarized variables:
-
su_y_cigexp__neg_001
-
su_y_cigexp__neg_002
-
-
Excluded values:
0
-
Validation criterion: maximally 0 of 2 items missing
Usage
vars_su_y_cigexp__neg
compute_su_y_cigexp__neg_prsum(
data,
name = "su_y_cigexp__neg_prsum",
combine = TRUE,
exclude = c("0"),
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_cigexp__neg is a character vector of all column names
used to compute summary score of su_y_cigexp__neg_prsum
and
su_y_cigexp__neg_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of positive expectancies): Prorated sum"
Description
Computes the summary score su_y_cigexp__pos_prsum
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Prorated sum
Note: all 0s are changed to NAs prior to calculating pro-rated sum
-
Summarized variables:
-
su_y_cigexp__pos_001
-
su_y_cigexp__pos_002
-
su_y_cigexp__pos_003
-
su_y_cigexp__pos_004
-
-
Excluded values:
0
-
Validation criterion: maximally 2 of 4 items missing
Usage
vars_su_y_cigexp__pos
compute_su_y_cigexp__pos_prsum(
data,
name = "su_y_cigexp__pos_prsum",
combine = TRUE,
exclude = c("0"),
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_cigexp__pos is a character vector of all column names
used to compute summary score of su_y_cigexp__pos_prsum
and
su_y_cigexp__pos_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Drug Problem Index (DAPI) [Youth]: Prorated sum"
Description
Computes the summary score su_y_drgprob_prsum
Drug Problem Index (DAPI) [Youth]: Prorated sum [Validation: No more
than 3 missing or declined]
-
Summarized variables:
-
su_y_drgprob_001
-
su_y_drgprob_002
-
su_y_drgprob_003
-
su_y_drgprob_004
-
su_y_drgprob_005
-
su_y_drgprob_006
-
su_y_drgprob_007
-
su_y_drgprob_008
-
su_y_drgprob_009
-
su_y_drgprob_010
-
su_y_drgprob_012
-
su_y_drgprob_013
-
su_y_drgprob_014
-
su_y_drgprob_015
-
su_y_drgprob_016
-
su_y_drgprob_017
-
su_y_drgprob_018
-
-
Excluded values: none
-
Validation criterion: maximally 3 items missing
Usage
vars_su_y_drgprob
compute_su_y_drgprob_prsum(
data,
name = "su_y_drgprob_prsum",
combine = TRUE,
max_na = 3
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_drgprob is a character vector of all column names
used to compute summary score of su_y_drgprob_prsum
and
su_y_drgprob_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative expectancies): Prorated sum"
Description
Computes the summary score su_y_mjexp__neg_prsum
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative
expectancies): Prorated sum [Validation: No more than 1
missing or declined]
-
Summarized variables:
-
su_y_mjexp__neg_001
-
su_y_mjexp__neg_002
-
su_y_mjexp__neg_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 3 items missing
Usage
vars_su_y_mjexp__neg
compute_su_y_mjexp__neg_prsum(
data,
name = "su_y_mjexp__neg_prsum",
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_mjexp__neg is a character vector of all column names
used to compute summary score of su_y_mjexp__neg_prsum
and
su_y_mjexp__neg_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive expectancies): Prorated sum"
Description
Computes the summary score su_y_mjexp__pos_prsum
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive
expectancies): Prorated sum [Validation: No more than 1
missing or declined]
-
Summarized variables:
-
su_y_mjexp__pos_001
-
su_y_mjexp__pos_002
-
su_y_mjexp__pos_003
-
-
Excluded values: none
-
Validation criterion: maximally 1 of 3 items missing
Usage
vars_su_y_mjexp__pos
compute_su_y_mjexp__pos_prsum(
data,
name = "su_y_mjexp__pos_prsum",
combine = TRUE,
max_na = 1
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_mjexp__pos is a character vector of all column names
used to compute summary score of su_y_mjexp__pos_prsum
and su_y_mjexp__pos_nm
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Problem Index (MAPI) [Youth]: Prorated sum"
Description
Computes the summary score su_y_mjprob_prsum
Marijuana Problem Index (MAPI) [Youth]: Prorated sum [Validation: No more
than 3 missing or declined]
-
Summarized variables:
-
su_y_mjprob_001
-
su_y_mjprob_002
-
su_y_mjprob_003
-
su_y_mjprob_004
-
su_y_mjprob_005
-
su_y_mjprob_006
-
su_y_mjprob_007
-
su_y_mjprob_008
-
su_y_mjprob_009
-
su_y_mjprob_010
-
su_y_mjprob_011
-
su_y_mjprob_012
-
su_y_mjprob_016
-
su_y_mjprob_017
-
su_y_mjprob_018
-
-
Excluded values: none
-
Validation criterion: maximally 3 items missing
Usage
vars_su_y_mjprob
compute_su_y_mjprob_prsum(
data,
name = "su_y_mjprob_prsum",
combine = TRUE,
max_na = 3
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_mjprob is a character vector of all column names
used to compute summary score of su_y_mjprob_prsum
and
su_y_mjprob_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Subjective Response and Effects [Youth] (Total): Sum - Positive score inverted [Validation: None missing or declined]"
Description
Computes the summary score su_y_mjsre_sum
Marijuana Subjective Response and Effects [Youth] (Total): Sum -
Positive score inverted [Validation: None missing or declined]
-
Summarized variables:
-
su_y_mjsre__pos_001
-
su_y_mjsre__pos_002
-
su_y_mjsre__pos_003
-
su_y_mjsre__neg_001
-
su_y_mjsre__neg_002
-
su_y_mjsre__neg_003
-
su_y_mjsre__neg_004
-
su_y_mjsre__neg_005
-
su_y_mjsre__neg_006
-
su_y_mjsre__neg_007
-
su_y_mjsre__neg_008
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 11 items missing
Usage
vars_su_y_mjsre
compute_su_y_mjsre_sum(
data,
name = "su_y_mjsre_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_mjsre is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Subjective Response and Effects [Youth] (Negative): Sum [Validation: None missing or declined]"
Description
Computes the summary score su_y_mjsre__neg_sum
Marijuana Subjective Response and Effects [Youth] (Negative): Sum
[Validation: None missing or declined]
-
Summarized variables:
-
su_y_mjsre__neg_001
-
su_y_mjsre__neg_002
-
su_y_mjsre__neg_003
-
su_y_mjsre__neg_004
-
su_y_mjsre__neg_005
-
su_y_mjsre__neg_006
-
su_y_mjsre__neg_007
-
su_y_mjsre__neg_008
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 8 items missing
Usage
vars_su_y_mjsre__neg
compute_su_y_mjsre__neg_sum(
data,
name = "su_y_mjsre__neg_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_mjsre__neg is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre__neg
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Marijuana Subjective Response and Effects [Youth] (Positive): Sum [Validation: None missing or declined]"
Description
Computes the summary score su_y_mjsre__pos_sum
Marijuana Subjective Response and Effects [Youth] (Positive): Sum
[Validation: None missing or declined]
-
Summarized variables:
-
su_y_mjsre__pos_001
-
su_y_mjsre__pos_002
-
su_y_mjsre__pos_003
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 3 items missing
Usage
vars_su_y_mjsre__pos
compute_su_y_mjsre__pos_sum(
data,
name = "su_y_mjsre__pos_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_mjsre__pos is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre__pos
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Intensity of positive and negative effects of first smokeless tobacco or chew use): Sum - Negative score inverted [Validation: None missing or declined]"
Description
Computes the summary score su_y_nicsre__chew_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first smokeless tobacco or chew use): Sum -
Negative score inverted [Validation: None missing or declined]
-
Summarized variables:
-
su_y_nicsre__chew__pos_001
-
su_y_nicsre__chew__neg_001
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
vars_su_y_nicsre__chew
compute_su_y_nicsre__chew_sum(
data,
name = "su_y_nicsre__chew_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_nicsre__chew is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__chew
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Intensity of positive and negative effects of first cigarette use): Sum - Negative score inverted [Validation: None missing or declined]"
Description
Computes the summary score su_y_nicsre__cig_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first cigarette use): Sum - Negative score
inverted [Validation: None missing or declined]
-
Summarized variables:
-
su_y_nicsre__cig__pos_001
-
su_y_nicsre__cig__neg_001
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
vars_su_y_nicsre__cig
compute_su_y_nicsre__cig_sum(
data,
name = "su_y_nicsre__cig_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_nicsre__cig is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__cig
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "Nicotine Subjective Response and Effects [Youth] (Intensity of positive and negative effects of first vape use): Sum - Negative score inverted [Validation: None missing or declined]"
Description
Computes the summary score su_y_nicsre__vape_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first vape use): Sum - Negative score
inverted [Validation: None missing or declined]
-
Summarized variables:
-
su_y_nicsre__vape__pos_001
-
su_y_nicsre__vape__pos_001__v01
-
su_y_nicsre__vape__neg_001
-
su_y_nicsre__vape__neg_001__v01
-
-
Excluded values: none
-
Validation criterion: maximally 0 of 2 items missing
Usage
vars_su_y_nicsre__vape
compute_su_y_nicsre__vape_sum(
data,
name = "su_y_nicsre__vape_sum",
combine = TRUE,
max_na = 0
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
Format
vars_su_y_nicsre__vape is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__vape
(_sum
, _nm
).
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "ENDS Expectancies [Youth] (Strength of negative expectancies): Prorated sum"
Description
Computes the summary score su_y_nicvapeexp__neg_prsum
ENDS Expectancies [Youth] (Strength of negative expectancies):
Prorated sum [Validation: No more than 2 missing or declined]
-
Summarized variables:
-
su_y_nicvapeexp__neg_001
-
su_y_nicvapeexp__neg_002
-
su_y_nicvapeexp__neg_003
-
su_y_nicvapeexp__neg_004
-
-
Excluded values: none
-
Validation criterion: maximally 2 of 4 items missing
Usage
vars_su_y_nicvapeexp__neg
compute_su_y_nicvapeexp__neg_prsum(
data,
name = "su_y_nicvapeexp__neg_prsum",
combine = TRUE,
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_nicvapeexp__neg is a character vector of all column names
used to compute summary score of su_y_nicvapeexp__neg_prsum
and
su_y_nicvapeexp__neg_nm
Value
tbl. The input data frame with the summary score appended as a new column.
Compute "ENDS Expectancies [Youth] (Strength of positive expectancies): Prorated sum"
Description
Computes the summary score su_y_nicvapeexp__pos_prsum
ENDS Expectancies [Youth] (Strength of positive expectancies):
Prorated sum [Validation: No more than 2 missing or declined]
-
Summarized variables:
-
su_y_nicvapeexp__pos_001
-
su_y_nicvapeexp__pos_002
-
su_y_nicvapeexp__pos_003
-
su_y_nicvapeexp__pos_004
-
-
Excluded values: none
-
Validation criterion: maximally 2 of 4 items missing
Usage
vars_su_y_nicvapeexp__pos
compute_su_y_nicvapeexp__pos_prsum(
data,
name = "su_y_nicvapeexp__pos_prsum",
combine = TRUE,
max_na = 2
)
Arguments
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
Format
vars_su_y_nicvapeexp__pos is a character vector of all column names
used to compute summary score of su_y_nicvapeexp__pos_prsum
and
su_y_nicvapeexp__pos_nm
.
Value
tbl. The input data frame with the summary score appended as a new column.