[R] GlmmPQL

[O Tosas Auguet]

Dear all,


I have two questions concerning model simplification in GlmmPQL, for for random
and fixed effects:

1. Fixed effects: I don't know if I can simply specify anova(model) and trust
the table that comes up with the p value for each variable  in the fixed
effects formula. I have read that the only way to test for fixed effects is to
do approximate wald tests based on the standard errors of the models where I am
subsequently withdrawing one variable from the fixed effect formula at a time.
What does "aproximate" wald test mean? What is the best option?

2. Random effects: If AIC is not meaningful in GlmmPQL, how do I test for the
significance of the random effects?

3. I way to see if 1 single level of random effects is helpful in terms of
analysing the data, would be to comapre the GlmmPQL model with a glm models
without random effects, but again: what do I compare if AIC is not meaninful?
and if there is something I can compare, could I test for the significance of
that difference?

Could someone bring light to this?

Thanks,

Olga Tosas