R/mcpPV.R

In musto101/wilcox_R: What the package does (short line)

mcpPV <-
function(pv,alpha=.05,opt=1){
#
#  pv: A collection of p-values based on independent tests
#
#  Perform the step-down multiple comparison method in 
#  Wilcox, R. R. \& Clark, F. (in press).
#   Robust multiple comparisons based on combined
#    probabilities from independent tests.  Journal of Data Science
#  based on K independent p-values
#
#  opt=1  Fisher's method
#  opt=2  Chen-Nadarajah method
#  opt=3  Max method
#
K=length(pv)
pick=NULL
v=order(pv)
ic=0
for(i in K:1){
flag=TRUE
if(opt==1){
i2=i*2
if(i==K)res=(0-2)*sum(log(pv))  # Fisher test statistic
if(i<K)res=(0-2)*sum(log(pv[-pick]))  # Fisher test statistic
pvF=1-pchisq(res,i2)   #Fisher p-value based on all tests.
}
if(opt==2){
if(i==K)res=sum(qnorm(pv/2)^2)  # C-N test
if(i<K)res=sum(qnorm(pv[-pick]/2)^2)
pvF=1-pchisq(res,i)
}
if(opt==3){
if(i==K)res=max(pv)
if(i<K)res=max(pv[-pick])
pvF=pbeta(res,i,1)
}
if(pvF>alpha)flag=TRUE
if(pvF<=alpha/(K+1-i)){
ic=ic+1
pick=c(pick,v[ic])
flag=FALSE
if(pv[v[ic]]>alpha)flag=TRUE
}
if(flag)break
}
Decision=rep('Not Sig',length(pv))
if(!is.null(pick))Decision[pick]='Reject'
nsig=sum(length(pick))
list(p.values=pv,
Decisions=as.matrix(Decision),num.sig=nsig)
}