[R-sig-ME] overdispersion estimation in a binomial GLMM

[Thomas Merkling]

Dear list members,

I am trying to fit a binomial GLMM and I wonder if there is 
overdispersion. I'm not sure to know how to do it. I tried to fit with 
"quasibinomial" family but apparently it doesn't exist anymore in lme4.

I also tried this but I am not sure that it is true for mixed models.

model<-lmer(propNb~SexA*SexB*AgeA+(1|Nest),data=baba,family="binomial")

k <- attr(logLik(model),"df") #
n <- length(fitted(model))
pearsonresid <- (1/(n-k)) * sum(resid(model,"pearson")^2) # 1.731892
dev <- deviance(model)/(n-k) #2.378512

One more thing: how to deal with this model if there is overdispersion ?

Thanks by advance,
Best,

-- 
Thomas Merkling, Doctorant (PhD Student)

Laboratoire "Evolution et Diversité Biologique" -EDB
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Université Paul Sabatier Toulouse 3
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