[R] type III sums of squares in R

[Stefanie von Felten, IPW&IfU]

Hi everyone,

Can someone explain me how to calculate SAS type III sums of squares in 
R? Not that I would like to use them, I know they are problematic. I 
would like to know how to calculate them in order to demonstrate that 
strange things happen when you use them (for a course for example). I 
know you can use drop1(lm(), test="F") but for an lm(y~A+B+A:B), type 
III SSQs are only calculated for the A:B interaction. If I specify 
lm(y~A+B), it calculates type II SSQ for the main effects (as type III 
only differs from type II if interactions are included). Thus, this 
approach doesn't help.

Another approach is the Anova(, type="III") function within the 
library(car). But somehow it produces strange results. Somebody told me 
I have to change the contrast settings using
options(contrasts=c("contr.helmert", "contr.poly"))
 But I had the impression that my results are still impossible.
Are the calculations dependent from the version of R I use? I am 
currently using R2.1.1

The only thing that seems to work is a trick: Specify a separate column 
AB that codes a new variable for the interaction of A:B. Now you can fit 
A,B, and AB (as 3 main effects) in 3 different sequential models with 
each one of them in the end once. For the term in the end you then get 
type III SSQ which seem to be correct.

Cheers
Steffi

-- 
---------------------------------
Stefanie von Felten
Doktorandin

ETH Zürich
Institut für Pflanzenwissenschaften
Universitätstrasse 2, LFW A2
8092 Zürich
Telefon: 044 632 85 97
Telefax: 044 632 11 53
e-mail: stefanie.vonfelten at ipw.agrl.ethz.ch

Universität Zürich
Institut für Umweltwissenschaften
Winterthurerstrasse 190
8057 Zürich
Telefon: 044 635 61 23
Telefax: 044 635 57 11
e-mail:  sfelten at uwinst.unizh.ch