<alicia.senauer <at> yale.edu> writes: > > I am trying to use R lm() with quantitative and qualitative predictors, but am > getting different results than those that I get in SAS. > > In the R ANOVA table documentation I see that "Type-II tests corresponds to > the > tests produced by SAS for analysis-of-variance models, where all of the > predictors are factors, but not more generally (i.e., when there are > quantitative predictors)." Is this the problem? Is there a way around this so > that the output matches the results that I am getting in SAS? Is there a > better/more appropriate way to handle quantitative predictors?
First of all, it looks you're using Anova, in the car package -- this is an important piece of information. Second, you're presumably (you didn't tell us exactly what commands you ran -- this is also important) using the default type="II" in Anova, vs. SAS type III sums of squares (as it says in your SAS output), so I wouldn't expect these to agree. Third, it's highly questionable whether type-III SS are appropriate here, in the presence of an interaction (Treat*Plant) -- you have violated "marginality restrictions" -- see http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf for example. While I understand the desire to match the output from SAS, a better set of questions is "why do these two disagree? What are they doing differently? Which one comes closer to answering the questions I am really interested in?" Ben Bolker ______________________________________________ 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.