Hi, the following is my R code, where drastic discrepancy is shown between the significant adjusted p values obtained from "mt.maxT (W&Y strong control of FWER)" and "mt.rawp2adjp" (4932 vs. 0). Would you please tell me why this happens, as I really do not know where is the bug in my code? Much Thanks > ################################################################## > #mt.maxT procedure:compute permutation adjusted p-values # > #for W&Y step-down multiple testing procedures # > ################################################################## > resTPBvsP2<-mt.maxT(theta.PBvsP2,classlabel=cl.PBvsP2,test="pairt",s ide="abs",B=10000) We're doing 10000 random permutations b=100 b=200 b=300 b=400 b=500 b=600 b=700 b=800 b=900 ...b=10000 > no.rawpTPBvsP2<-sum(resTPBvsP2$rawp<0.05);print(no.rawpTPBvsP2) [1] 4932 > no.adjpTPBvsP2<-sum(resTPBvsP2$adjp<0.05);print(no.adjpTPBvsP2) [1] 0 > > ordTPBvsP2<-order(resTPBvsP2$index) > ################################################################## > #rows are sorted first according to their adjusted p-values # > #next their unadjusted p values and finally their test statistics# > #i.e. resTPBvsP2$adjp==sort(resTPBvsP2$adjp) ################################################################## > rawpTPBvsP2<-resTPBvsP2$rawp[ordTPBvsP2] > #original data order, to be used in mt.rawp2adjp procedure# > > ############################################ > #mt.rawp2adjp:computes adjusted p-values # > #for simple multiple testing procedures # > #from a vector of raw (unadjusted) p-values# > ############################################ > resPBvsP2T<- mt.rawp2adjp(rawpTPBvsP2, proc = c("Holm"))#FWER# > no.adjpPBvsP2T<-sum(resPBvsP2T$adjp<0.05);print(no.adjpPBvsP2T) [1] 4932 Thank you, Anqi [[alternative HTML version deleted]]