Title: Providing Demographic Table with the P-Value, Standardized Mean Difference Value
Version: 0.1.0
Description: The Demographic Table in R combines contingency table for categorical variables, mean and standard deviation for continuous variables. t-test, chi-square test and Fisher's exact test calculated the p-value of two groups. The standardized mean difference were performed with 95 % confident interval, and writing table into document file.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: officer, magrittr, MASS, stats
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-01-05 00:14:28 UTC; loanrobinson
Author: Loan Robinson [aut, cre]
Maintainer: Loan Robinson <loankimrobinson@gmail.com>
Repository: CRAN
Date/Publication: 2019-01-09 17:30:07 UTC

smd value for categorical variables

Description

smd value for categorical variables

Usage

cat_smd(ntable, var, data)

Arguments

ntable

propotion table of baseline categorical variable and group variable

var

baseline categorical variable

data

data

Examples

set.seed(2018)
group <-round(abs(rnorm(500)*10),0) %% 2
cont_1 <-round(abs(rnorm(500)*10),0)
cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3
data_check <-data.frame(group, cont_1, cat_multi_1)
data_check$group <- factor(data_check$group, levels = c(0,1), labels = c("Control","Treatment"))
data_check$cat_multi_1 <- factor(data_check$cat_multi_1)
cat_smd(table(data_check$cat_multi_1, data_check$group),"cat_multi_1",data_check )

DemoGraphic table for categorical variables

Description

DemoGraphic table for categorical variables

Usage

cat_table(var, strata, data)

Arguments

var

baseline variables

strata

group variable with 1 = treatment and 0 = control

data

data

Examples

set.seed(2018)
group <-round(abs(rnorm(500)*10),0) %% 2
cont_1 <-round(abs(rnorm(500)*10),0)
cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3
data_check <-data.frame(group, cont_1, cat_multi_1)
data_check$group <- factor(data_check$group, levels = c(0,1), labels = c("Control","Treatment"))
data_check$cat_multi_1 <- factor(data_check$cat_multi_1)
cat_table("cat_multi_1","group",data_check )

smd value for continuous variable.

Description

smd value for continuous variable.

Usage

cont_smd(mean1, mean2, var1, var2)

Arguments

mean1

mean of a baseline variable in the treatment group.

mean2

mean of a baseline variable in the control group.

var1

variance a baseline variable in the treatment group.

var2

variance of a baseline variable in the control group.

Value

smd value

Examples

cont_smd(10,11,2,3)

DemoGraphic table for continuous variables

Description

DemoGraphic table for continuous variables

Usage

cont_table(var, strata, data)

Arguments

var

variables

strata

group variable with 1 = treatment and 0 = control

data

data

Value

mean, standard deviation of treatmant and control group, smd, and p value.

Examples

set.seed(2018)
group <-round(abs(rnorm(500)*10),0) %% 2
cont_1 <-round(abs(rnorm(500)*10),0)
cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3
data_check <-data.frame(group, cont_1, cat_multi_1)
data_check$group <- factor(data_check$group, levels = c(0,1), labels = c("Control","Treatment"))
data_check$cat_multi_1 <- factor(data_check$cat_multi_1)
cont_table("cont_1","group", data_check )

Demographic Table for continuous and categorical variables

Description

Demographic Table for continuous and categorical variables

Usage

demo_table(var, strata, data)

Arguments

var

list of baseline variables

strata

group variable with 1 = treatment and 0 = control

data

data

Examples

set.seed(2018)
group <-round(abs(rnorm(500)*10),0) %% 2
cont_1 <-round(abs(rnorm(500)*10),0)
cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3
data_check <-data.frame(group, cont_1, cat_multi_1)
data_check$group <- factor(data_check$group, levels = c(0,1), labels = c("Control","Treatment"))
data_check$cat_multi_1 <- factor(data_check$cat_multi_1)
demo_table(c("cont_1","cat_multi_1"),"group", data_check )

Mean, var function

Description

Mean, var function

Usage

get_mean(x)

Arguments

x

variable

Value

mean table

Examples

get_mean(round(abs(rnorm(500)*10),0))

chi square test to get expected value and p value

Description

chi square test to get expected value and p value

Usage

my.chi.sq(...)

Arguments

...

variables

Examples

set.seed(2018)
group <-round(abs(rnorm(500)*10),0) %% 2
cont_1 <-round(abs(rnorm(500)*10),0)
cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3
data_check <-data.frame(group, cont_1, cat_multi_1)
data_check$group <- factor(data_check$group, levels = c(0,1), labels = c("Control","Treatment"))
data_check$cat_multi_1 <- factor(data_check$cat_multi_1)
my.chi.sq(table(data_check$cat_multi_1, data_check$group))

fisher exact test to get p value if any cell in propotion table of expect value less than 5

Description

fisher exact test to get p value if any cell in propotion table of expect value less than 5

Usage

my.fisher(...)

Arguments

...

variables

Examples

set.seed(2018)
data_check <-data.frame(
  group <-round(abs(rnorm(500)*10),0) %% 2,
  cat_multi_1 <-round(abs(rnorm(500)*10),0) %% 3)
my.fisher(table(data_check$cat_multi_1, data_check$group))

write smd table or demographic table into docx file

Description

write smd table or demographic table into docx file

Usage

mydocx(smd_table, name)

Arguments

smd_table

smd table or demo graphic table.

name

file name to save

Examples

mydocx(data.frame(smd.value <- 3.4, smd.lo <- 1.1, smd.up <- 5.6),"smd_table")

Confident interval for smd

Description

Confident interval for smd

Usage

smd_ci(n1, n2, smd)

Arguments

n1

length of a baseline variable in the treatment group.

n2

length of a baseline variable in the control group.

smd

smd value

Value

vector of 95

Examples

smd_ci(10,12,0.3)

t.test to calculate p value

Description

t.test to calculate p value

Usage

## S3 method for class 'test.p.value'
t(...)

Arguments

...

variables

Value

p value