Hello everyone,

I hope my questions are not too basic...

I'm trying to run a binomial GLMM (binary response variable) with glmer 
and I have different results when comparing the summary of my full model 
and likelihood ratio tests with anova(model1,model2).
In Bolker et al 2009, they advised to use Wald test to test for fixed 
effects.
Are the p-values in the summary Wald Z-tests results ? Is there any way 
to choose which kind of Wald test we want in R when testing for fixed 
effects in a generalized mixed effects model?

I also wanted to use MC techniques to have more accurate estimation of 
the estimates and their confidence intervals, but I couldn't use 
mcmcsamp function neither mcsamp function. What are the other 
possibilities ?

Finally, I tried to use MCMCglmm package, despite my poor familiarity 
with these techniques (maybe a mistake). When specifying 
family="categorical" (as my response variable is binary) the plot of the 
traces were really bad , while there were really better with 
family="gaussian". Does it make any sense ? Not really to me ...
Moreover, I also have a problem with one of the 2 random effects (traces 
stucked at zero). It has only 5 levels and I think I read that there 
might some problems with random effects with few levels. How to deal 
with this kind of problem ?

Thanks in advance for your help !
Thomas
-- 
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Thomas Merkling, Doctorant (PhD Student)
Web Page <http://www.edb.ups-tlse.fr/Merkling-Thomas.html>

Laboratoire "Evolution et Diversité Biologique" -EDB
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Université Paul Sabatier Toulouse 3
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31062 TOULOUSE Cedex O9, FRANCE

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