overdispersion estimation in a binomial GLMM

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 Diversit? Biologique" -EDB
UMR 5174 - b?t 4R3 b2 - bureau 226

Universit? Paul Sabatier Toulouse 3
118, route de Narbonne
31062 TOULOUSE Cedex O9, FRANCE

T?l: 33 5-61-55-67-58
Fax: 33 5-61-55-73-27