[R] Degrees of freedom in repeated measures glmmPQL

From: Charlotte Burn <charlotteburn_at_googlemail.com>
Date: Wed, 02 May 2007 12:09:10 +0100


Hello,

I've just carried out my first good-looking model using glmmPQL, and the output makes perfect sense in terms of how it fits with our hypothesis and the graphical representation of the data. However, please could you clarify whether my degrees of freedom are appropriate?

I had 106 subjects,
each of them was observed about 9 times, creating 882 data points. The subjects were in 3 treatment groups, so I have told the model to include subject as a random factor nested within treatment. There are two other variables and I'm interested in their two-way interactions with Treatment.
I'm happy with the model structure, and the output generally looks right, but...

In the 'DF' column of the output table, it has 882 as the degrees of freedom for all the variables (except Treatment itself, which has 0 degrees of freedom). At the bottom of the output, it says Groups: Subjects = 106, Treatment = 3.

Should I be worried or is this what to expect?!

I was expecting it to be more like an ANOVA table, where the error degrees of freedom should reflect the number of subjects, not all the data points.

I can't see the usual differentiation between the numerater and denominator/error degrees of freedom, so am I right in thinking the DF column shows the error degrees of freedom? Or do glmms not work like this?

Thank you very much in advance,
Charlotte



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