wilcox_R: What the package does (short line)

yuen.effect <-
function(x,y,tr=.2,alpha=.05,plotit=FALSE,
plotfun=splot,op=TRUE,VL=TRUE,cor.op=FALSE,
xlab="Groups",ylab="",PB=FALSE){
#
#  Same as yuen, only it computes explanatory power and the related
# measure of effect size. Only use this with n1=n2. Called by yuenv2
# which allows n1!=n2.
#
#
#  Perform Yuen's test for trimmed means on the data in x and y.
#  The default amount of trimming is 20%
#  Missing values (values stored as NA) are automatically removed.
#
#  A confidence interval for the trimmed mean of x minus the
#  the trimmed mean of y is computed and returned in yuen$ci.
#  The significance level is returned in yuen$siglevel
#
#  For an omnibus test with more than two independent groups,
#  use t1way.
#  This function uses winvar from chapter 2.
#
if(tr==.5)stop("Use medpb to compare medians.")
if(tr>.5)stop("Can't have tr>.5")
library(MASS)
x<-x[!is.na(x)]  # Remove any missing values in x
y<-y[!is.na(y)]  # Remove any missing values in y
h1<-length(x)-2*floor(tr*length(x))
h2<-length(y)-2*floor(tr*length(y))
q1<-(length(x)-1)*winvar(x,tr)/(h1*(h1-1))
q2<-(length(y)-1)*winvar(y,tr)/(h2*(h2-1))
df<-(q1+q2)^2/((q1^2/(h1-1))+(q2^2/(h2-1)))
crit<-qt(1-alpha/2,df)
m1=mean(x,tr)
m2=mean(y,tr)
mbar=(m1+m2)/2
dif=m1-m2
low<-dif-crit*sqrt(q1+q2)
up<-dif+crit*sqrt(q1+q2)
test<-abs(dif/sqrt(q1+q2))
yuen<-2*(1-pt(test,df))
xx=c(rep(1,length(x)),rep(2,length(y)))
pts=c(x,y)
top=var(c(m1,m2))
#
if(!PB){
if(tr==0)cterm=1
if(tr>0)cterm=area(dnormvar,qnorm(tr),qnorm(1-tr))+2*(qnorm(tr)^2)*tr
bot=winvar(pts,tr=tr)/cterm
}
if(PB)bot=pbvar(pts)/1.06
#
e.pow=top/bot
if(e.pow>1){
x0=c(rep(1,length(x)),rep(2,length(y)))
y0=c(x,y)
e.pow=wincor(x0,y0,tr=tr)$cor^2
}
if(plotit){
plot(xx,pts,xlab=xlab,ylab=ylab)
if(op)
points(c(1,2),c(m1,m2))
if(VL)lines(c(1,2),c(m1,m2))
}
list(ci=c(low,up),p.value=yuen,dif=dif,se=sqrt(q1+q2),teststat=test,
crit=crit,df=df,Var.Explained=e.pow,Effect.Size=sqrt(e.pow))
}