Hello, Thank you very much for your response!
However, I still do not understand how this works. I would like to adjust the factors (diagnosis and gender) for the covariate (age), so you are saying I should use: aov.out <- aov(response ~ age + diagnosis*gender, data) or aov.out <- aov(response ~ age*diagnosis*gender, data) But how is that different from just a 3-way ANOVA with age, diagnosis, and gender as the the three effects? Isn't ANCOVA a fundamentally different model? Thanks, Sasha On 8/23/06, Richard M. Heiberger <[EMAIL PROTECTED]> wrote: > > aov.out <- aov(response~diagnosis*gender,data) > > Just add it where you think it belongs in the > sequential sum of squares > > To adjust the factors for the covariate use > aov.out <- aov(response ~ age + diagnosis*gender, data) > > To adjust the covariate for the factors > aov.out <- aov(response ~ diagnosis*gender + age, data) > > If you want to check for interaction of the factors with the > covariate, then use * instead of + in the formula. > > Please note that I added spaces to your statement to improve human legibility. > > Rich > ______________________________________________ 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.