[R-sig-ME] How to assess significance of variance components(Please discard previous e mail... but read this one)

[Stephane Chantepie]

Hi,

Thank David for the package reference. 

Sorry, I did not recall the context of my work but I am doing animal models on  
Poisson distributed traits. So I have to use MCMCglmm package -and 
consequently I am in a Bayesian framework).

I want to test an increased in genetic variance (VA) by AGE. The major issue 
come from the fact that univariate models using age-classes show a decrease 
with VA across age and the random regression show an increase with age. I want 
to test the accuracy of AGExVA parameter of the random regression.

-MCMCglmm give posterior distributions well shape for all parameters of each 
model, so it cannot be a criterion of rejecting a model. 
-According to Jarrod, DIC is not usable with Poisson distribution trait.

I am unable to decide if univariate or RR which provide the best explicable 
results. 

Have someone an idea to define a criterion? 

thank in advance


Stephane