I am getting a repeated error when I try to run a logistic regression in R 2.8.1
>(glm(prop1~x1,data=glm1,family=binomial("logit"),weights=nt1)) Error in model.frame.default(formula = prop1 ~ x1, data = glm1, weights = nt1, : invalid type (list) for variable 'x1' x1 is multistate categorical (3 categories). 2 of the categories have 12 observation, one has 9. Is this what it is objecting to? Do I have to have equal numbers of observations of all categories in R? nt1 is the total number of events for which p1 is the success proportion, each is linked with a category, vis.. > list(glm1) [[1]] V1 V1 V1 1 1.00000000 cc 10 2 0.73333333 cc 15 3 0.04761905 cc 21 etc.... Probably a newbie error either in data setup, but assistacne would be appreciated. Ned -- View this message in context: http://www.nabble.com/logistic-regression---unequal-groups-in-R-tp22215299p22215299.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.