Emmanuelle TASTARD <tastard <at> cict.fr> writes:
>
> Hi,
> Im sorry, I know that it is a recurrent question but I have not been
> able to find the response in the Rhelp archives.
> I think my data require the use of the glmmPQL function but I do not
> know how to make the model selection. Since the AIC and log-likelihood
> are apparently meaningless, how can we select the parameters for a model
> and compare the models to find which one fits best the data?
I think your choices are (1) use the estimated standard errors/p-values
of the fixed effects to decide whether to include them in the model
or (2) if you really need likelihood-based tests, use lmer.
(Model selection for variance parameters is a can of worms, see
Pinheiro and Bates.) Also remember that *all* methods for this kind
of model are approximations, it's just a question of which ones are
more accurate (generally and in particular situations).
That's just my best guess, someone else may have better advice ...
cheers
Ben Bolker
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