Dears, I'd like asking your help to understand a statistical issue from my data set. I ran a GLM with proportional data, using a binomial distribution. However, I've found?underdispersion?in my model and I don't know how to deal with that. I'm aware that a solution for overdispersion is fit a model using a quasibinomial distribution, but I couldn't find in the literature a solution to my problem. I'd really thank if you can help me. Cheers, Mauricio [[alternative HTML version deleted]]
Mauricio Gomes <almeida.gomes <at> yahoo.com.br> writes:> > > Dears, > I'd like asking your help to understand a statistical issue > from my data set. I ran a GLM with proportional > data, using a binomial distribution. However, > I've found?underdispersion?in my model and I don't > know how to deal with that. I'm aware that a solution > for overdispersion is fit a model using a > quasibinomial distribution, but I couldn't find in the l > iterature a solution to my problem. I'd really > thank if you can help me. > Cheers, > MauricioThis is really more of a statistical than a programming question, but short answer: quasi-likelihood estimation (i.e. familyquasibinomial) should address underdispersion and well as overdispersion reasonably well.
wrong list. Post on stats.stackexchange.com -- Bert Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." Clifford Stoll On Sat, Jan 24, 2015 at 1:53 AM, Mauricio Gomes <almeida.gomes at yahoo.com.br> wrote:> > Dears, > I'd like asking your help to understand a statistical issue from my data set. I ran a GLM with proportional data, using a binomial distribution. However, I've found underdispersion in my model and I don't know how to deal with that. I'm aware that a solution for overdispersion is fit a model using a quasibinomial distribution, but I couldn't find in the literature a solution to my problem. I'd really thank if you can help me. > Cheers, > Mauricio > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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.