Matthew Bridgman wrote: > Why would someone use lm and ANOVA (anova(lm(x))) instead of AOV (or > the other way around)? > The mean squares and sum of squares are the same, but the F values > and p-values are slightly different. > > Crudely put, aov() is effectively useless on unbalanced designs. On the other hand, it will allow you to handle models with multistratum error structure.
I am somewhat at a loss as to how you manage to get the same MS and SS but different F. Presumably, the denominator is different, but if you're not messing with Error() terms, then I believe both aov() and anova(lm()) would use the residual MS. An example might help. > I am modeling a dependent~independent1*independent2. > > Thanks, > Matt Bridgman > [[alternative HTML version deleted]] > > ______________________________________________ > [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 > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ [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 and provide commented, minimal, self-contained, reproducible code.
