[R-sig-ME] MCMCglmm, priorR and binomial distribution

[Camille Madec]

Dear everyone,

I have a model with 2 fixed factors, 1 random factor and a binary  
response variable. I ran a MCMCglmm with family=”categorical” and the  
prior for the residual being R=list(V=1, nu=0.002). In the summary of  
the model I got high post.mean values (around 50 for fixed effects and  
 >1000 for random effects and sometimes up to 14000).
I ran the same model with R=list(V=1, fix=1) which means that the  
variance of the residual is fixed to 1, so the residual becomes a  
fixed factor (if I understand correctly). In that case my post.mean  
values are smaller (between zero and 24).

My questions are:
1) Are the large values in the first case normal?
2) How do I know which prior is the more appropriate for the residual?

Bests,
Camille

-----
Camille Madec
PhD student
Plant Ecology and Evolution
Uppsala University
Sweden