Dear Jarrod, recently you suggested that to overcome overdispersion in a binomial distribution by fitting a observation-level random effect. I was wondering if this method has been described anywhere so I can put a reference in my report.
Thanks a lot, Greetings David Jansen Hi Thierry + nameless, It is not necessary to expand the binomial into Bernoulli trials (nor advisable if n and/or the binomial size are large). You can just fit observation-level random effects: dataset$resid<-as.factor(1:dim(dataset)[1]) fit3<- glmer(cbind(male_chick_no, female_chick_no) ~ 1+(1|FemaleID)+ (1|resid), data = dataset, family = binomial) gives the same answer as fit2 Cheers, Jarrod -- ---------------------------------------------- David Jansen PhD student in Vocal communication in banded mongoose ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
