[R] Degrees of freedom in repeated measures glmmPQL

[Charlotte Burn]

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