Dear Peter and Paul, As Paul discovered, Anova() doesn't handle aovlist objects.
As a general matter, one should be careful with "type-III" tests, since it's easy to test hypotheses that aren't sensible (e.g., tests ostensibly of main effects that aren't reasonably interpretable as tests of main effects). For example, SAS (and I assume SPSS) produce type-III tests in analysis of covariance that aren't generally sensible. I haven't thought about whether there's a similar trap in unbalanced repeated-measures ANOVA. By the way, sequential (or "type-I") tests are rarely sensible in my opinion. Regards, John > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Peter Dalgaard > Sent: Thursday, August 26, 2004 7:08 AM > To: Paul Lemmens > Cc: [EMAIL PROTECTED] > Subject: Re: [R] library(car) Anova() and Error-term in aov() > > Paul Lemmens <[EMAIL PROTECTED]> writes: > > > Dear all, > > > > Type III SS time again. This case trying to reproduce some > SPSS (type > > III) data in R for a repeated measures anova with a betwSS factor > > included. As I understand this list etc, if I want type III > then I can > > do > > > > library(car) > > Anova(lm.obj, type="III") > > > > But for the repeated measures anova, I need to include an > Error-term > > in the aov() call (Psychology-guide from Jonathan Baron) > which results > > in multiple lm() calls. Anova() does not seem capable to > handle this > > situation. Or am I tackling Type III calculation, in this case with > > Error(), the wrong way (besides ignoring advice concerning > Type I vs > > III)?? > > > > For instance, > > > > dat <- rnorm(12) > > pp <- factor(c(rep(1:3,2), rep(4:6,2))) betw <- gl(2,6) A <- > > factor(rep(c(rep('a',3),rep('b',3)), 2)) taov <- > > aov(dat~betw*A+Error(pp/A)) Anova(taov, type="III") # Goes > wrong with > > following error. > > #Error in Anova(taov, type = "III") : no applicable method > for "Anova" > > > > Phrased differently, ?Anova says "Calculates type-II or type-III > > analysis-of-variance tables for model objects produced by 'lm' and > > 'glm'", so it's not suitable for the aovlist that aov() with > > Error()-term returns. How can I compute Type III SS for > such objects? > > Well, ... > > In a balanced design you don't need Type III SS (because they > are all the same) -- summary(taov) will do. > > In an unbalanced design, you don't want to use aov() with an > Error term. (Slightly overstated, but you certainly get to > think very closely if the unbalance is in the Error model). > > I'm not actually sure what SPSS does in the case of > unbalanced designs (complete-case analysis?). > > In principle, with a balanced Error model, you should be able > to extract, say, taov[[2]] and do an Anova() or drop1() on > that, but it doesn't work because the object is not really an > "lm" object, even though > > > class(taov[[2]]) > [1] "aov" "lm" > > but we get things like > > > model.frame(as(taov[[2]],"lm")) > $method > lm > > > -- > O__ ---- Peter Dalgaard Blegdamsvej 3 > c/ /'_ --- Dept. of Biostatistics 2200 Cph. N > (*) \(*) -- University of Copenhagen Denmark Ph: > (+45) 35327918 > ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: > (+45) 35327907 > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html