Jeroen Ooms wrote:
> I would like to do a SS type III analysis on a proportional odds logistic
> regression model. I use drop1(), but dropterm() shows the same behaviour. It
> works as expected for regular main effects models, however when the model
> includes an interaction effect it seems to have problems with matching the
> parameters to the predictor terms. An example:
>
> library("MASS");
> options(contrasts = c("contr.treatment", "contr.poly"));
>
> house.plr1 <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data =
> housing);
> drop1(house.plr1,attributes(house.plr1$terms)$term.labels,test="Chisq");
>
> house.plr2 <- polr(Sat ~ Infl * Type + Cont, weights = Freq, data =
> housing);
> drop1(house.plr2,attributes(house.plr2$terms)$term.labels,test="Chisq");
>
> Notice that model 2 has a * instead of a + between predictors Infl and Type.
> In model 1, estimated parameters are nicely attributed to the right term,
> however in house.plr2, only 2 of the 4 terms are evaluated.
>
> I am using R version 2.7.2 (2008-08-25) i386-pc-mingw32, and MASS_7.2-44.
>
(It would have been better form to actually print the result so that
people can see what you're on about:
> drop1(house.plr2,attributes(house.plr2$terms)$term.labels,test="Chisq");
Single term deletions
Model:
Sat ~ Infl * Type + Cont
Df AIC LRT Pr(Chi)
<none> 3484.6
Infl 0 3484.6 2.086e-08
Type 0 3484.6 -1.301e-10
Cont 1 3497.8 15.1 0.0001009 ***
Infl:Type 6 3495.1 22.5 0.0009786 ***
I take it that the perceived problem is the two 0-Df lines.)
This is slightly peculiar, yes, but notice that in lm() or glm() you'd
normally just not get entries for main effects in the presence of their
interaction. This is deliberate -- type III tests can be seriously
misleading and/or uninterpretable in that case, so you really are better
off without them.
The direct cause of the behaviour above is that in R,
Infl+Type+Infl:Type
and
Type+Infl:Type
are just two parametrizations of the same model. Try
summary(house.plr2)
summary(update(house.plr2,~.-Type))
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
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