You may be able to get around zero cells using a an MCMC approach such as with MCMCglmm.
On Aug 4, 2012, at 15:30, Sacha Viquerat <dawa.ya.m...@googlemail.com> wrote: > On 08/04/2012 07:57 PM, Joshua Wiley wrote: >> Hi Sacha, >> >> You're right that this is not an R related question really (would be better >> somewhere like crossvalidated.com). >> >> If basically everyone catches 0/1 birds, then I would consider dichotomizing: >> >> Y <- as.integer(caught >= 1) >> >> then check cross tabs to make sure there are no zero cells between >> predictors and outcome: >> >> xtabs(~Y + dogs + guns, data=yourdata) >> >> then use the glmer() function to model the nested random effects. >> >> m <- glmer(Y ~ dog + gun + (1 | household) + (1 | village) + (1 | district), >> data = yourdata, family=binomial) >> >> summary(m) >> >> Cheers, >> >> Josh >> >> On Aug 4, 2012, at 7:12, Sacha Viquerat <dawa.ya.m...@googlemail.com> wrote: >> >>> Hello! >>> I am doing an analysis on a questionnaire of hunters taken in 4 different >>> districts of some mysterious foreign country. The aim of the study was to >>> gather info on the factors that determine the hunting success of a >>> peculiarly beautiful bird in that area. All variables are factors, i.e. >>> they are variables such as "Use of Guns - yes / no", "Use of Dogs - yes / >>> no" and the likes. The response is upposed to be "number of Birds caught", >>> which was designed to be the only continuous variable. However, in reality >>> the number of caught birds is between 0 and 1, sometimes hunters answered >>> with 2. Unfortunately, it is not the questioner who is burdened with the >>> analysis, but me. I am struggling to find an appropriate approach to the >>> analysis. I don't really consider this as count data, since it would be >>> very vulnerable to overinflation (and a steep decline for counts above 0). >>> I can't really suggest binomial models either, since the lack of >>> explanatory, continuous data renders such ! an approach quite vague. I also struggle with the random design of the survey (households nested within villages nested within districts). Adding to that, hunters don't even target the bird as their prime objective. The bird is essentially a by-catch, most often used for instant consumption on the hunting trip. I therefore doubt that any analysis makes more than a little sense, but I will not yet succumb to failure. Any ideas? >>> >>> Thanks in advance! >>> >>> PS: I just realized that this is not a question related to R but to >>> statistics in general. Apologies for that! >>> >>> ______________________________________________ >>> 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. > I did exactly what you proposed already (since the binomial model seemed > obvious to me), however, of course there are zero cells. I was thinking > someone more accustomed to doing questionnaire analysis could unveil some > mysterious approach common to sociologists but occluded from the naturalists > eyes (hardened after years of dealing with exact science ;) > I think I will expand the binomial approach and just try to find fancy > graphics that make up for the low value of the actual results (maybe with > colours). :D > Thank you for the reply (do they really give such tasks for homework these > days? These kids must be awesome statisticians!) > ______________________________________________ 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.
