# R/ES.t.paired.R In powerAnalysis: Power Analysis in Experimental Design

#### Documented in ES.t.paired

#' Calculating effect size (Cohen's d) of paired two-sample t test
#'
#' @param md          mean difference (e.g., mean(x-y))
#' @param sd          standard deviation of mean differences (e.g., sd(x-y))
#' @param n           number of paires
#' @param t           t statistic
#' @param se          standard error of mean differences
#' @param df          degree of freedom
#' @param alternative The test is two sided or one sided
#' @export
#' @examples
#' ## md, sd -> d
#' ES.t.paired(md=-0.08062384,sd=1.401886)
#'
#' ## md,se -> d
#' ES.t.paired(md=-0.08062384,se=0.1982566,n=50)
#'
#' ## t, df -> d
#' ES.t.paired(t=-0.4067,df=49)
#'
#' ## t, n -> d
#' ES.t.paired(t=-0.4067,n=50)
ES.t.paired <- function(md=NULL,sd=NULL,n=NULL,t=NULL,se=NULL,df=NULL,alternative = c("two.sided", "one.sided")){
alternative <- match.arg(alternative)
d <- NULL
if(sum(sapply(list(md,sd), is.null)) == 0){
d <- md/sd
}else if(sum(sapply(list(md,se,n), is.null)) == 0){
sd <- se * sqrt(n)
d <- md/sd
}else if(sum(sapply(list(t,df), is.null)) == 0){
d <- t / sqrt(df)
}else if(sum(sapply(list(t,n), is.null)) == 0){
d <- t / sqrt(n-1)
}
NOTE0="The alternative hypothesis is md > 0"
if(alternative =="two.sided"){
d <-abs(d)
NOTE0="The alternative hypothesis is md != 0"
}
NOTE1="small effect size:  d = 0.2"
NOTE2="medium effect size: d = 0.5"
NOTE3="large effect size:  d = 0.8"
NOTE=paste(NOTE0,NOTE1,NOTE2,NOTE3,sep="\n")
METHOD="effect size (Cohen's d) of paired two-sample t test"
structure(list(d = d, alternative = alternative, note=NOTE,method = METHOD), class = "power.htest")
}

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powerAnalysis documentation built on May 2, 2019, 12:40 p.m.