Dear Fredrik,

At 06:56 AM 3/8/2002 +0100, Fredrik Karlsson wrote:Hi all

I'm trying to complete a textbook example originally designed for SPSS

in R, and I therefore need to find out how to compute an unbalanced

ANOVA in R.

I did a search on the mailinglist archives an found a post by Prof.

Ripley saying one should use the lme function for (among other things)

unbalanced ANOVAs, but I have not been able to use this object.

My code gives me an error.. Why is that ?

aov(lme(DELAY ~ DOSE + TRIALS,data=epinuneq))

Error in getGroups.data.frame(dataMix, groups) :

Invalid formula for groups

Any ideas? How do I get an ANOVA computation that can handle uniqual

sampe sizes in R?

The lme function is designed for linear mixed models, that is, models

including both fixed and random effects. It's hard to tell from the

information that you provide whether a mixed model is appropriate for your

data -- in particular, is TRIALS a repeated-measures factor? If you indeed

need to fit a mixed model, then you haven't specified it correctly. See the

help page for lme for details.

On the other hand, if you just want to fit a fixed-effects Anova with no

interactions, then you can use the aov or lm functions. Again, see

help(aov) and help(lm). The summary method for aov and the anova method for

both aov and lm objects will give you sequential ("type I") sums of

squares. The Anova function in the car package can compute "Type II" and

"III" sums of squares for lm objects. If you use the latter, be careful

with the contrast coding.

I hope that this helps,

John

-----------------------------------------------------

John Fox

Department of Sociology

McMaster University

Hamilton, Ontario, Canada L8S 4M4

email: jfox at mcmaster.ca

phone: 905-525-9140x23604

web: www.socsci.mcmaster.ca/jfox

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