# R/yuend.R In WRS2: A Collection of Robust Statistical Methods

```yuend <- function(x, y, tr = 0.2){
#
#  Compare the trimmed means of two dependent random variables
#  using the data in x and y.
#  The default amount of trimming is 20%
#
#  Any pair with a missing value is eliminated
#  The function rm2miss allows missing values.
#
#  A confidence interval for the trimmed mean of x minus the
#  the trimmed mean of y is computed and returned in yuend\$ci.
#  The significance level is returned in yuend\$p.value
#
#  This function uses winvar from chapter 2.
#
cl <- match.call()
alpha=.05
if(length(x)!=length(y))stop("The number of observations must be equal")
m<-cbind(x,y)
m<-elimna(m)
x<-m[,1]
y<-m[,2]
h1<-length(x)-2*floor(tr*length(x))
q1<-(length(x)-1)*winvar(x,tr)
q2<-(length(y)-1)*winvar(y,tr)
q3<-(length(x)-1)*wincor(x,y,tr)\$cov
df<-h1-1
se<-sqrt((q1+q2-2*q3)/(h1*(h1-1)))
crit<-qt(1-alpha/2,df)
dif<-mean(x,tr)-mean(y,tr)
low<-dif-crit*se
up<-dif+crit*se
test<-dif/se
yuend<-2*(1-pt(abs(test),df))
epow <- yuenv2(x,y,tr=tr)\$Effect.Size

result <- list(test = test, conf.int = c(low,up), se = se, p.value = yuend, df = df, diff = dif, effsize = epow, call = cl)
class(result) <- "yuen"
result
}
```

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WRS2 documentation built on May 2, 2019, 4:46 p.m.