hi. i did some research first, but didn't find what i was looking for... the thing is: i generated data with correlated errors and simulated the power with using aov(). what i wanna do now is something similar while using lme(), so that the corr-structure will be paid attention to. i'm not quite sure how to do that... i hope someone can help me. thanks in advance. mel code: ee<-mvrnorm(n=100, mu=rep(0,N),Omega.block) #omega.block describes the corr-structure mu<-c(1,2,3) (group<-factor(rep(1:k,n))) eval.simu<-function(e) { y<-mu[group]+e fit<-aov(y~group) s.fit<-summary(fit)[[1]] s.fit$P[1] } p<-apply(ee,1,"eval.simu") #then count number of p?alpha to get power -- View this message in context: http://www.nabble.com/simulate-data-for-lme-tp18342119p18342119.html Sent from the R help mailing list archive at Nabble.com.