thanks for your answer! For the butterfly counts we used butterfly bait traps. They were not visible counts. I read several ecological papers that treat species or individuals counts as Poisson applying GLM rather than e.g. repeated measures ANOVA. I assumed that the monthly collection out of a species pool cannot be independent. To choose GEE was my idea because of its advantage for repeated measures and Poisson distribution...
2011/8/29 Prof Brian Ripley <rip...@stats.ox.ac.uk> > You need to tell use why you want to use a GEE model. From your use of > corstr = "ar1" I would surmise you think the counts are serially correlated > during a year (despite the presence of a 'month' main effect), in which case > the id is 'site'. > > All 'id' does is to partition the data into clusters: counts for different > clusters are independent, counts within a cluster are (potentially) > dependent. > > The common advice applies: you should talk to a statistician conversant > with GEE models about your model formulation. (My field experience would > suggest that there is no good reason to suppose that the counts are Poisson: > visible occurrences of butterfly species do not behave independently.) > > > On Mon, 29 Aug 2011, Anna Mill wrote: > > Hi all, >> >> I am trying to do a generalized estimating equation (GEE) with the >> "geepack" >> package and I am not 100% sure what exactly the "id" argument means. It >> seems to be an important argument because results differ considerably >> defining different clusters. >> >> I have a data set of counts (poisson distribution): numbers of butterfly >> species counted every month during a period of one year (12 repeated >> measures) at seven sites, three of those being "continuous forest sites" >> and >> four of those being "secondary forest sites". The aim is to compare >> continuous and secondary forests. >> >> Would you define the sites or the forest type as id argument: >> >> model1<-geeglm(formula = number ~ type + month, family = poisson, *id = >> site >> *, corstr = "ar1") >> >> model2<-geeglm(formula = number ~ type + month, family = poisson, *id = >> type >> *, corstr = "ar1") >> >> or should even almost every count have a special id (e.g. * >> id=interaction(month,site)* or *id=interaction(month,type*)) >> >> Thanks for your help... >> Anna >> >> [[alternative HTML version deleted]] >> >> ______________________________**________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help> >> PLEASE do read the posting guide http://www.R-project.org/** >> posting-guide.html <http://www.R-project.org/posting-guide.html> >> and provide commented, minimal, self-contained, reproducible code. >> >> > -- > Brian D. Ripley, rip...@stats.ox.ac.uk > Professor of Applied Statistics, > http://www.stats.ox.ac.uk/~**ripley/<http://www.stats.ox.ac.uk/%7Eripley/> > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > [[alternative HTML version deleted]] ______________________________________________ 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.
