You would not use a Poisson distribution, you would use a binomial, since the number of positives is not in (0,\inf) but in (0,broilers).
So you would de a random-effects logistic regression. I guess an attractive approach would be to use the MCMCglmm package that will do this sort of model using an MCMC approach. Best regards, Bendix Carstensen > -----Original Message----- > From: r-sig-epi-boun...@stat.math.ethz.ch > [mailto:r-sig-epi-boun...@stat.math.ethz.ch] On Behalf Of > dieter.anseeuw > Sent: 17. august 2010 07:29 > To: r-sig-epi@stat.math.ethz.ch > Subject: [R-sig-Epi] random-effects modeling > > Hi all, > > > > Being new to analysing epidemiologic data, I have a question > about the following data set: > > A friend has inspected three randomly chosen farms (random > factor 'farm'). At each farm three randomly chosen series of > chickens (random factor 'flock') were each inspected for the > presence of a certain bacteria. The contaminated chickens > were counted (response variable 'positives'). The sample > sizes per flock are given by 'broilers'. We want to have a > look at within-broilers, within-farm and between-farm variability. > > > > It seems to me that we have a random-effects model, in which > the factor 'flock' is nested within the factor 'farm'. Am I > correct so far? > > Now, since the response variable yields count data, fitting > the model should be done using Poisson regression. Correct? > > > > Could somebody help me out with (an example of) such an analysis? > > > > Many thanks in advance, > > Dieter > > > > Here is the dataset used: > > > > broilers<-data.frame(farm=c("FA","FA","FA","FB","FB","FB","FC" ,"FC","FC"), flock=c("a","b","c","d","e","f","g","h","i"), > broilers=c(50, rep(25,8)), positives=c(7,2,0,7,2,0,0,5,2)) > > > > > > -- > > Dieter Anseeuw > > Katho Campus Roeselare > > Wilgenstraat 32 > > 8800 Roeselare Belgium > > > > Direct phone: +32 51 23 29 68 > > http://www.katho.be/hivb > > http://www.linkedin.com/in/dieteranseeuw > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Epi@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-epi > _______________________________________________ R-sig-Epi@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-epi
