Hi all (and especially Frank), I'm trying to use x=T, y=T in order to run a validated stepwise cox regression in rsm, having multiply imputed using mice. I'm coding
model.max<-fit.mult.impute(baseform,cph,miced2,dated.sexrisk2,x=T,y=T) baseform is baseform<-Surv(si.age,si=="Yes")~ peer.press + copy.press + excited + worried + intimate.friend + am.pill.times + info.parents + info.teacher + info.sch.nurse + info.friends + info.media + info.clinic + info.gp + info.fpa + info.chemist + nearer.clinic + uti + thrush + herpes + love + strat(gender) + Own.space + ordered(Chat.Mother) + ordered(Chat.Father) + ordered(Prts.interested) + ordered(Someone.stands.up.4u) + Thought.runaway + as.numeric(Prts.know.location)+ pubty + partner + arguments + mfqc.total + esteem.total + events.total + bmi This gives the error message Error in 1:n.impute : NA/NaN argument In addition : Warning message: In 1:n.impute : numerical expression has 130 elements: only the first used :> It doesn't seem to be a singularity problem, as the simple equation model.test<-fit.mult.impute(Surv(si.age,si=="Yes")~peer.press,cph,miced2,dated.sexrisk2,x=T,y=T) gives an identical message, and the code runs perfectly in either without x=T, y=T PS the dataset is 827 rows x 130 variables. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.