Convert numeric to string with uppercase first letter

Description

Convert numeric to string with uppercase first letter

Usage

English(x, digits = 2)

Arguments

Value

A string

Examples

English(40)
English(13.1)

Demographic data of 857 patients with ACS

Description

A dataset containing demographic data and laboratory data of 857 patients with acute coronary syndrome(ACS).

Usage

acs

Format

An object of class data.frame with 857 rows and 17 columns.

Examples

interpretCI::acs

Draw normal distribution curve

Description

Draw normal distribution curve

Usage

draw_n(mean = 0, sd = 1, z = NULL, p = 0.05, alternative = "two.sided")

Arguments

Value

A ggplot

Examples

draw_n()
draw_n(alternative="less")
draw_n(alternative="greater")
draw_n(z=-1.75)
draw_n(z=-1.75,alternative="greater")
draw_n(z=-1.75,alternative="less")

Draw t distribution curve

Description

Draw t distribution curve

Usage

draw_t(DF = 50, t = NULL, p = 0.05, alternative = "two.sided")

Arguments

Value

A ggplot

Examples

draw_t(DF=30)
draw_t(DF=20,t=2.5)
draw_t(DF=49,t=1.77)
draw_t(DF=49,p=0.005)
draw_t(DF=19,t=-0.894,alternative="less")
draw_t(DF=146,t=0.67,alternative="greater")

Convert numeric to string

Description

Convert numeric to string

Usage

english2(x, digits = 2)

Arguments

Value

A character string

Examples

english2(45)
english2(12.34)

Draw estimation plot1

Description

Draw estimation plot1

Usage

estimationPlot1(x, palette = NULL)

Arguments

Value

A ggplot

Examples

x=meanCI(iris,Species,Sepal.Length)
estimationPlot1(x)

Interpret an object of meanCI

Description

Interpret an object of meanCI. Render appropriate rmarkdown file to html file and show RStudio viewer or browser.

Usage

interpret(x, viewer = "rstudio")

Arguments

Value

No return value, called for side effect

Examples

x=meanCI(mtcars$mpg)
x=meanCI(mtcars,mpg,mu=23)
x=meanCI(n=150,m=115,s=10,alpha=0.01)
x=meanCI(n=50,m=295,s=20,mu=300)
x= meanCI(n=20,m=108,s=10,mu=110,alpha=0.01,alternative="less")
x=meanCI(n1=500,n2=1000,m1=20,s1=3,m2=15,s2=2,alpha=0.01)
x=meanCI(n1=15,n2=20,m1=1000,s1=100,m2=950,s2=90,alpha=0.1)
x=meanCI(n1=30,n2=25,m1=78,s1=10,m2=85,s2=15,mu=0,alpha=0.10)
x=meanCI(n1=100,n2=100,m1=200,s1=40,m2=190,s2=20,mu=7,alpha=0.05,alternative="greater")
x1=c(95,89,76,92,91,53,67,88,75,85,90,85,87,85,85,68,81,84,71,46,75,80)
y1=c(90,85,73,90,90,53,68,90,78,89,95,83,83,83,82,65,79,83,60,47,77,83)
x=meanCI(x=x1,y=y1,paired=TRUE,alpha=0.1,mu=0)
x=propCI(n=1600,p=0.4,alpha=0.01)
x=propCI(n=100,p=0.73,P=0.8,alpha=0.01)
x=propCI(n=100,p=0.73,P=0.8,alpha=0.05,alternative="greater")
x=propCI(n1=100,n2=200,p1=0.38,p2=0.51,alpha=0.01)
x=propCI(n1=150,n2=100,p1=0.71,p2=0.63,P=0,alternative="greater")
## Not run: 
interpret(x)
interpret(x,"browser")

## End(Not run)

Decide whether a vector can be treated as a numeric variable

Description

Decide whether a vector can be treated as a numeric variable

Usage

is.mynumeric(x, maxy.lev = 5)

Arguments

Value

logical

Examples

x=1:5
is.mynumeric(x)
x=1:13
is.mynumeric(x)

Whether the arg is provided in function call

Description

Whether the arg is provided in function call

Usage

isProvided(x, seek = "mu")

Arguments

Value

logical

Examples

x=meanCI(mtcars,am,mpg)
isProvided(x)

Calculate confidence intervals of mean or difference between means

Description

Calculate confidence intervals of mean or difference between means

Usage

meanCI(x, ...)

Arguments

Value

An object of class "meanCI" which is a list containing at least the following components:

data

A tibble containing raw data or a list of numeric vector

result

A data.frame consist of summary statistics

call

the matched call

attr(*,"measure")

character. One of c("mean","unpaired","paired")

Examples

meanCI(mtcars$mpg)
meanCI(n=150,m=115,s=10,alpha=0.01)
meanCI(n=50,m=295,s=20,mu=300)
meanCI(n=20,m=108,s=10,mu=110,alpha=0.01,alternative="less")
meanCI(mtcars,am,mpg)
meanCI(n1=15,n2=20,m1=1000,s1=100,m2=950,s2=90,alpha=0.1)
meanCI(n1=500,n2=1000,m1=20,s1=3,m2=15,s2=2,alpha=0.01)
meanCI(n1=30,n2=25,m1=78,s1=10,m2=85,s2=15,alpha=0.10)
meanCI(n1=100,n2=100,m1=200,s1=40,m2=190,s2=20,mu=7,alpha=0.05,alternative="greater")
x=c(3.04,2.92,2.86,1.71,3.60,3.49,3.30,2.28,3.11,2.88,2.82,2.13,2.11,3.03,3.27,2.60,3.13)
y=c(2.56,3.47,2.65,2.77,3.26,3.00,2.70,3.20,3.39,3.00,3.19,2.58,2.98)
meanCI(x=x,y=y)
x=c(95,89,76,92,91,53,67,88,75,85,90,85,87,85,85,68,81,84,71,46,75,80)
y=c(90,85,73,90,90,53,68,90,78,89,95,83,83,83,82,65,79,83,60,47,77,83)
meanCI(x=x,y=y,paired=TRUE,alpha=0.1)
meanCI(10:30,1:15)
meanCI(acs,sex,age)
meanCI(iris$Sepal.Width,iris$Sepal.Length)
meanCI(iris$Sepal.Width,iris$Sepal.Length,paired=TRUE)

Calculate confidence intervals of mean or difference between means in a data.frame

Description

Calculate confidence intervals of mean or difference between means in a data.frame

Usage

## S3 method for class 'data.frame'
meanCI(x, ...)

meanCI_sub(data = data, x, y, group, paired = FALSE, idx = NULL, ...)

Arguments

Value

An object of class "meanCI" which is a list containing at least the following components:

data

A tibble containing raw data or a list of numeric vector

result

A data.frame consists of summary statistics

call

the matched call

attr(*,"measure")

character. One of c("mean","unpaired","paired")

Methods (by generic)

• meanCI: S3 method for data.frame

Examples

meanCI(acs,age)
meanCI(acs,sex,age)
meanCI(acs,Dx,age)
acs %>% select(age) %>% meanCI()
acs %>% select(sex,age) %>% meanCI()
meanCI(iris,Species,Sepal.Length)
meanCI(iris,Sepal.Width,Sepal.Length,paired=TRUE)
meanCI(iris,Sepal.Length,Sepal.Width)
iris %>% select(starts_with("Petal")) %>% meanCI(paired=TRUE)
iris %>% meanCI(paired=TRUE)
meanCI(acs,sex,age,Dx,mu=10)
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(group=sex)
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(sex)
iris %>% select(Species,starts_with("Sepal")) %>% meanCI(Species)
iris %>% select(Species,starts_with("Sepal")) %>% meanCI(group=Species)

Calculate confidence intervals of mean or difference between means

Description

Calculate confidence intervals of mean or difference between means

Usage

## Default S3 method:
meanCI(x, ...)

meanCI2(
  x,
  y,
  n,
  m,
  s,
  n1,
  n2,
  m1,
  m2,
  s1,
  s2,
  mu = 0,
  paired = FALSE,
  var.equal = FALSE,
  alpha = 0.05,
  digits = 2,
  alternative = "two.sided"
)

Arguments

Value

An object of class "meanCI" which is a list containing at least the following components:

data

A tibble containing raw data or a list of numeric vector

result

A data.frame containing of summary statistics

call

the matched call

attr(*,"measure")

character. One of c("mean","unpaired","paired")

Methods (by generic)

• meanCI: Default S3 method

Prepare data to plot from an object of class meanCI

Description

Prepare data to plot from an object of class meanCI

Usage

meanCI2df(x)

Arguments

Value

A data.frame

Examples

x=meanCI(acs,sex,age)
meanCI2df(x)

Extract data from an object of class meanCI

Description

Extract data from an object of class meanCI

Usage

meanCI2df1(x)

Arguments

Value

A data.frame summarizing mean and confidence interval

Examples

x=meanCI(acs,sex,age)
meanCI2df1(x)

Draw meanCI plot for data with single vector

Description

Draw meanCI plot for data with single vector

Usage

meanCIplot1(x)

Arguments

Value

A ggplot

Examples

x=meanCI(mtcars,mpg)
meanCIplot1(x)

Draw a pair plot with an object of class meanCI

Description

Draw a pair plot with an object of class meanCI

Usage

pairPlot(x, palette = NULL)

Arguments

Value

A ggplot

Examples

x=meanCI(iris,paired=TRUE)
pairPlot(x)
x=meanCI(iris,Petal.Width, Petal.Length,paired=TRUE)
pairPlot(x)

Draw a pair plot

Description

Draw a pair plot

Usage

pairPlot1(data, ref = NULL, palette = NULL)

Arguments

Value

A ggplot

Examples

x=meanCI(mtcars,paired=TRUE)
pairPlot1(x$data)
pairPlot1(x$data,ref=c(1,4,6))
pairPlot1(x$data,ref=c(1,3))

Extract hexadecimal colors from a color palette

Description

Extract hexadecimal colors from a color palette

Usage

palette2colors(name, reverse = FALSE)

Arguments

Value

hexadecimal colors

Examples

palette2colors("Reds")

S3 method for an object of class "meanCI"

Description

S3 method for an object of class "meanCI"

Usage

## S3 method for class 'meanCI'
plot(x, ref = "control", side = NULL, palette = NULL, ...)

Arguments

Value

A ggplot or an object of class "plotCI" containing at least the following components: '

p1

A ggplot

p2

A ggplot

side

logical

Examples

meanCI(mtcars,mpg) %>% plot()
meanCI(mtcars,am,mpg) %>% plot()
meanCI(iris,Sepal.Width) %>% plot()
meanCI(iris,Sepal.Width,Sepal.Length) %>% plot()

meanCI(iris,Sepal.Width,Sepal.Length,paired=TRUE) %>% plot(palette="Dark2")
meanCI(iris,Sepal.Width,Sepal.Length) %>% plot()
meanCI(iris,Species,Sepal.Width) %>% plot(side=TRUE)
meanCI(iris,Species,Sepal.Width,mu=0.5,alternative="less") %>% plot(ref="test")
meanCI(acs,age) %>% plot()
meanCI(acs,sex,age) %>% plot()
meanCI(acs,smoking,age) %>% plot(palette="Set1")
meanCI(acs,Dx,age) %>% plot()
meanCI(acs,Dx,age,sex,mu=0) %>% plot(palette="Dark2")
x=c(95,89,76,92,91,53,67,88,75,85,90,85,87,85,85,68,81,84,71,46,75,80)
y=c(90,85,73,90,90,53,68,90,78,89,95,83,83,83,82,65,79,83,60,47,77,83)
meanCI(x=x,y=y,paired=TRUE,alpha=0.1) %>% plot()
meanCI(10:30,1:15) %>% plot()
iris %>% meanCI() %>% plot(side=TRUE)
meanCI(n=150,m=115,s=10,alpha=0.01) %>% plot()
meanCI(n1=30,n2=25,m1=78,s1=10,m2=85,s2=15,alpha=0.10) %>% plot()
data(anscombe2,package="PairedData")
meanCI(anscombe2,idx=list(c("X1","Y1"),c("X4","Y4"),c("X3","Y3"),c("X2","Y2")),
paired=TRUE,mu=0) %>% plot()
x=meanCI(anscombe2,idx=list(c("X1","X2","X3","X4"),c("Y1","Y2","Y3","Y4")),paired=TRUE,mu=0)
plot(x)
longdf=tidyr::pivot_longer(anscombe2,cols=X1:Y4)
x=meanCI(longdf,name,value,idx=list(c("X1","X2","X3","X4"),c("Y1","Y2","Y3","Y4")),paired=TRUE,mu=0)
plot(x)
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(group=sex) %>% plot()
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(sex) %>% plot()

S3 method "print" for class "meanCI"

Description

S3 method "print" for class "meanCI"

Usage

## S3 method for class 'meanCI'
print(x, ...)

Arguments

Value

No return value, called for side effect

S3 method for class plotCI

Description

S3 method for class plotCI

Usage

## S3 method for class 'plotCI'
print(x, ...)

Arguments

Value

No return value, called for side effect

Calculate confidence intervals of proportion or difference between proportions

Description

Calculate confidence intervals of proportion or difference between proportions

Usage

propCI(
  x,
  y,
  n,
  p,
  n1,
  n2,
  p1,
  p2,
  P = 0,
  alpha = 0.05,
  digits = 2,
  alternative = "two.sided"
)

Arguments

Value

A list containing at least the following components:

data

A tibble containing raw data or a list of numeric vector

result

A data.frame consists of summary statistics

call

the matched call

attr(*,"measure")

character. One of c("prop","propdiff")

#'@examples propCI(acs$sex) propCI(acs$sex,acs$DM) propCI(n=1600,p=0.4,alpha=0.01) propCI(n=100,p=0.73,P=0.8,alpha=0.01) propCI(n1=400,n2=300,p1=0.4,p2=0.3,alpha=0.1) propCI(n1=100,n2=200,p1=0.38,p2=0.51,alpha=0.01) propCI(n1=100,n2=200,p1=0.38,p2=0.51,alpha=0.01,alternative="less")

Calculate confidence intervals of proportion or difference between proportions in a data.frame

Description

Calculate confidence intervals of proportion or difference between proportions in a data.frame

Usage

propCI_sub(data, x, y = NULL)

Arguments

Value

A list containing at least the following components:

data

A tibble containing raw data or a list of numeric vector

result

A data.frame consists of summary statistics

call

the matched call

attr(*,"measure")

character. One of c("prop","propdiff")

Examples

propCI_sub(acs,"sex")
propCI_sub(acs,"sex","HBP")

Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

dplyr

%>%, select

Show html file in RStudio viewer or browser

Description

Show html file in RStudio viewer or browser

Usage

rstudio_viewer(file_name, file_path = NULL, viewer = "rstudio")

Arguments

Value

No return value, called for side effect

Show t-value table

Description

Show t-value table

Usage

show_t_table(DF = 20, p = 0.05, alternative = "two.sided")

Arguments

Value

An object of class "flextable"

Examples

show_t_table()

Show z-value table

Description

Show z-value table

Usage

show_z_table(p = 0.05, alternative = "two.sided")

Arguments

Value

An object of class "flextable"

Examples

show_z_table()
show_z_table(p=0.01)

Draw textbox

Description

Draw textbox

Usage

textBox(
  string,
  color = "black",
  lcolor = "red",
  bg = "cornsilk",
  lwd = 1,
  width = 10,
  bold = FALSE,
  italic = FALSE,
  fontsize = 11,
  space = 1.5,
  fontname
)

Arguments

Value

A flextable

Examples

string="Good Morning!"
textBox(string,italic=TRUE)