On Feb 1, 2015, at 8:26 AM, JvanDyne wrote: > I am trying to use Poisson regression to model count data with four > explanatory variables: ratio, ordinal, nominal and dichotomous – x1, x2, x3 > and x4. After playing around with the input for a bit, I have formed – what > I believe is – a series of badly fitting models probably due to > overdispersion [1] - e.g. model=glm(y ~ x1 + > x2,family=poisson(link=log),data=data1) - and I was looking for some general > guidance/direction/help/approach to correcting this in R. > > [1] – I believe this as a. it’s, as I’m sure you’re aware, a possible reason > for poor model fits; b.the following: > > tapply(data1$y,data$x2,function(x)c(mean=mean(x),variance=var(x))) > > seems to suggest that, whilst variance does appear to be some function of > the mean, there is a consistently large difference between the two >
This is possibly an interesting question, but at the moment it is both off-topic on R and probably deserving of a book chapter as an answer. There are simply no specifics. One place where it would be on-topic and if tightened up with a specific example might prompt interesting and useful answers from a knowledgeable audience would be http://CrossValidated.com . > > Sent from the R help mailing list archive at Nabble.com. The Nabble "archive" of R-help is neither an archive of any sort since they arbitraily delte postings and not is most certainly not "the" Rhelp archive. Maybe if I unquote this four line message, then Nabble users will see it, although usually it get s trimmed: R-help@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. -- David Winsemius Alameda, CA, USA ______________________________________________ R-help@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.