On Sat, 13 Sep 2008, roberto toro wrote:
Hello, I've used this command to analyse changes in brain volume: mod1<-aov(Volume~Sex*Lobe*Tissue+Error(Subject/(Lobe*Tissue)),data.vslt) I'm comparing males/females. For every subject I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). As aov() provides only type I anovas, I would like to use lmer() with type II, however, I have struggled to find the right syntaxis. How should I write the model I use with aov() using lmer()?? Specifying Subject as a random effect is straightforward mod2<-lmer(Volume~Sex*Lobe*Tissue+(1|Subject),data.vslt) but I can't figure out the /(Lobe*Tissue) part...
You're trying to model a separate effect of lobe, of tissue, and of the interaction between lobe and tissue for each subject, so you want mod2<-lmer(Volume~Sex*Lobe*Tissue+(Lobe*Tissue|Subject),data.vslt) ...the resulting fixed effect for Lobe, Tissue, and L:T in the summary() then corresponds to the within-subjects effect aggregated (but not exactly AVERAGED) across subjects. So, it's not exactly providing you a Type II ANOVA...it's doing a mixed-effects model (or HLM, if you prefer), which as you've written it is a Type III analysis (though once again, not an ANOVA in the classical sense). To get something more akin to type II using the lmer function (and I trust someone will pipe up if there is a better way), you could first fit mod2.additive<-lmer(Volume~Sex*Lobe+Tissue+(Lobe+Tissue|Subject),data.vslt) ...and interpret the coefficients and effects provided by it, then fit the crossed model to get the coefficients and effects for the higher-order terms. I hope this made sense and that I have understood you correctly. --Adam ______________________________________________ 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.
