Hello,
I am teaching a graduate course on statistics for ecologists, one of whose
topics is GLMM.  I explain to the students the issue (somewhat recurrent in
this list) of why p values of fixed effects are not provided in lmer due to
the dispute/uncertainty on how to count degrees of freedom for random
effects. DBates, among others, have answered queries in this regard several
times. In this case, I explain how to use mcmcsamp to obtain p-values and
Conf Intervals for the fixed effects using Bayesian approaches when
family=Gaussian.

When one uses lmer for dist other than Gaussian the p-values of fixed
effects are actually printed. My question is WHY would these p-values for
family != Gaussian  be correct and adequate. I have searched for an answer
in the mailings of this list, but could not find one. Nor in my own library
and in many web searches. Is it because the function mcmcsamp currently
only accepts dist=Gaussian? To my mind, the p-values of fixed effects would
be subject to the same issues and "problems" regardless of the prob
distribution used in the analysis, because these issues arise from having a
mixed model.

Also, mcmcsamp only seems to accept a random effects structure having
random slopes and intercepts that are independent by construction. This
forces the user to fit a different (and often less adequate) model in order
to use the function mcmcsamp to obtain the p-values and conf Intervals of
fixed effects.

Advance apologies if this is a double posting and if these questions are on
the silly/pointless realm.

I would appreciate any help/suggestions on these two questions.

Regards,

Pablo Inchausti

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