S Ellison wrote: > >>>> Peter Dalgaard <[EMAIL PROTECTED]> 14/09/2007 09:26:16 >>> >>>> >>> So what can I do now to solve my problem? >>> >>> Do you think I should not use paired=TRUE? >>> >> You *can* only use it when you have pairs, and you must do it then, to >> correct for intra-pair correlation. The drawback is that it looks only >> at complete pairs, throwing away all the singlets. It is possible to >> recover the information from the singlets , basically by combining a >> paired test for the pairs and an unpaired one for the singlets. (Someone >> must have written this down, but I'm afraid I don't have a nice reference). >> > > Question: Could you achieve this kind of outcome with lme? stack the two > groups, mark the observations y by subject (ie the pair ID) and group > (treatment, presumably), and do something like > > anova(lme(y~group, data=d, random=~1|subj, na.action=na.omit)) > > Or is that just disguising one of those nasty unbalanced 2-way anova problems? > Yes, but....
I don't think lme() will do better than what you can do by hand: Get two independent estimates of mu1-mu2 (one estimate from the pairs and one from the singlets), compute a weighted average using the s.e.'s and test that against zero (possibly after testing them for equality for good measure). This is easy if you use a plug-in approach: first assume that the s.e. are known, then plug in their empirical value. The tricky bit is to calculate the DF in the style of Welch's test. -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ 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.
