I'm trying to make a glmm to identify the relationship between insect species richness with fragment size, isolation and time (different years). I already tried to analyse it using poisson distribution error, but I always face with the following warning: *glm.fit: fitted probabilities numerically 0 or 1 occurred * This is probably hapenning because my dataset has a lot of zeros. So, what error distribution should I use? -- *Lívia * [[alternative HTML version deleted]]
Could you please post a small example of your data and code which gives you this error. Your assumed error distribution sounds reasonable. I am interested as to why you have zeros... you have sites with species richness ==0 ?? L?via Dorneles Audino wrote> > I'm trying to make a glmm to identify the relationship between insect > species richness with fragment size, isolation and time (different years). > I already tried to analyse it using poisson distribution error, but I > always face with the following warning: > *glm.fit: fitted probabilities numerically 0 or 1 occurred * > > This is probably hapenning because my dataset has a lot of zeros. So, what > error distribution should I use? > > -- > *L?via * > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@ 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. >-- View this message in context: http://r.789695.n4.nabble.com/What-error-distribution-should-I-use-tp4509479p4510351.html Sent from the R help mailing list archive at Nabble.com.
L?via Dorneles Audino <livia.audino <at> gmail.com> writes:> > I'm trying to make a glmm to identify the relationship between insect > species richness with fragment size, isolation and time (different years). > I already tried to analyse it using poisson distribution error, but I > always face with the following warning: > *glm.fit: fitted probabilities numerically 0 or 1 occurred * > > This is probably hapenning because my dataset has a lot of zeros. So, what > error distribution should I use? >I know you haven't gotten a lot of help on r-sig-mixed-models (sorry), but it would probably be better to post this question there. The answer is that this is a warning, not an error, so it indicates a need for caution but not necessarily that anything is wrong. In this case, an internal call to glm.fit() has difficulty when it tries to fit a subset of that data that are all-zero or all-one. It's quite possibly OK, provided that you've looked at your results, plotted predicted values, etc., and everything seems to make sense.