On Apr 3, 2011, at 09:24 , Krishna Kirti Das wrote: > I have a three-way unbalanced ANOVA that I need to calculate (fixed effects > plus interactions, no random effects). But word has it that aov() is good > only for balanced designs. I have seen a number of different recommendations > for working with unbalanced designs, but they seem to differ widely (car, > nlme, lme4, etc.). So I would like to know what is the best or most usual > way to go about working with unbalanced designs and extracting a reliable > ANOVA table from them in R?
Actually, without random effects, aov() is not too crazy, but you might as well use plain lm(). In both cases, the main point is that you need to be aware that there is no such thing as "the" ANOVA table: Sums of squares will depend on the order of testing, and there is nothing to do about that (except getting balanced data). Pragmatically, I'd test the three-factor interaction, then use drop1() on a model with two-factor interactions, if nothing glaringly obvious pops up, try reduction to additive model and then use drop1() again. Obviously, if significant interactions appear, you cannot just remove them and need to investigate what they mean. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
