I don't think, this has been answered:
> I'm trying to run a 3-way within-subject anova in lme with 3
> fixed factors (Trust, Sex, and Freq), but get stuck with handling
> the random effects. As I want to include all the possible random
> effects in the model, it would be something more or less
> equivalent to using aov
>
> > fit.aov <- aov(Beta ~
> Trust*Sex*Freq+Error(Subj/(Trust*Sex*Freq)),
> Model)
>
> However I'm not so sure what I should do in lme. Sure
>
> > lme(Beta ~ Trust*Sex*Freq, random = ~1|Subj, Model)
>
> works fine, but it only models the random effect of the
> intercept. I tried the following 4 possibilities:
If I understand correctly, you want to include the interactions between the
random and fixed terms? This is done like:
model.lme <- lme(Beta ~ Trust*Sex*Freq,
random = ~Trust*Sex*Freq|Subj, Model)
But this needs a lot of observations as quite a few parameters need to be
estimated! Possibly, you can not include the variable Sex in this, because I
assume that Subj is nested within Sex. If you just refer to within and between
subject effects and their corresponding degrees of freedom: you should see this
being handled automatically and correctly by lme e.g. in the output of anova
(model.lme)
Lorenz
-
Lorenz Gygax
Centre for proper housing of ruminants and pigs
Agroscope Reckenholz-Tänikon Research Station ART
Tänikon, CH-8356 Ettenhausen / Switzerland
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