I take it that a zero inflated negative binomial (i.e. Poisson) regression model is what you are trying to fit, aka ZIP? If so try looking at the documentation for the zicounts package for R, for one. Of course, you can also search on these keywords yourself, to find exactly what you want....
Regards, Mike -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of I.Szentirmai Sent: 23 February 2006 17:24 To: R-help@stat.math.ethz.ch Subject: [R] binomial models with too many 1s??? Dear R users, Does anyone know a solution for the problem when there are too many ones or zeros in the respons of a binomial model? I think this means that the data are over/under despersed and the result is very bad model fit. I'm using glmmPQL(family=quasibinomial) to fit a model to my data, but the model estimates are not in the range they should be due to overdispersion (or under?) What shall I do? Is there a model type for this kind of data? I would prefer to keep all may data, otherwise I could also select some of the ones so that their number will be equal to the number of zeros. But I don't thik this is the right way... Any help would be appreciated. Thanks, Istvan ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
