Thanks for the response! It is indeed a balanced design. The results are different in the sense all the F tests for main effects are not the same. Do you mean that a random interaction is modeled in the aov command? If so, what would be an equivalent command of aov to the one with lme?
Thanks, Gang On Aug 3, 2007, at 3:52 PM, Peter Dalgaard wrote: > Gang Chen wrote: >> I have a mixed balanced ANOVA design with a between-subject >> factor (Grp) and a within-subject factor (Rsp). When I tried the >> following two commands which I thought are equivalent, >> >> > fit.lme <- lme(Beta ~ Grp*Rsp, random = ~1|Subj, Model); >> > fit.aov <- aov(Beta ~ Rsp*Grp+Error(Subj/Rsp)+Grp, Model); >> >> I got totally different results. What did I do wrong? >> >> > Except for not telling us what your data are and what you mean by > "totally different"? > > One model has a random interaction between Subj and Rsp, the other > does not. This may make a difference, unless the interaction term > is aliased with the residual error. > > If your data are unbalanced, aov is not guaranteed to give > meaningful results. > > -pd ______________________________________________ R-help@stat.math.ethz.ch 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.
