Please read the Help for predict.glm carefully to make sure you are not confusing predicted response on the linear scale (log odds) with that on the probability scale.
The warning is just that: a warning. It means that you have fitted PROBABILITIES on the boundary, which might compromise the iterative fitting algorithm and inference thereon. Ergo: examine this carefully before bithely proceeding. -- Bert On Wed, Mar 2, 2011 at 8:10 AM, <pat...@gmx.de> wrote: > Hi there, > > I am encountering a problem with the GLM tool performing logistic regression. > After computing a warning appears, saying “glm.fit: fitted probabilities > numerically 0 or 1 occurred”. A prediction of new values confirms the problem > as the model does not produce regular probability estimates but values which > are way higher than 1 and lower than 0 in many cases. > I have tried both methods setting the family=binomial and > family=binomial(“logit”) so this can’t be the reason that causes the error. > > As an alternative solution I have considered to resort to the Logistic tool > from the RWeka package. The manual says that it exists for building > multinomial logistic regression models. I can’t image it would be a problem > but can anyone confirm that it indeed is possible to use the algorithm for > also computing binary models?! > > Best regards > > Patrick > -- > Schon gehört? GMX hat einen genialen Phishing-Filter in die > > ______________________________________________ > 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. > -- Bert Gunter Genentech Nonclinical Biostatistics ______________________________________________ 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.
