soren.fau...@biology.au.dk wrote: > Full_Name: Søren Faurby > Version: 2.4.1 and 2.7.2 > OS: > Submission from: (NULL) (192.38.46.92) > > > There appear to be a bug in the estimation of significance in the binomial > model > in GLM. This bug apparently appears when the correlation between two variables > is to strong. > > Such as this dummy example > c(0,0,0,0,0,1,1,1,1,1)->a > a->b > m1<-glm(a~b, binomial) > summary(m1) > > It is sufficient that all 1's correspond to 1's such as this example > > c(0,0,0,0,0,1,1,1,1,1)->a > c(0,0,0,0,1,1,1,1,1,1)->c > m1<-glm(a~c, binomial) > summary(m1)
That's not a bug, just the way things work. When the algorithm diverges, as seen by the huge Std.Error, Wald tests (z) are unreliable. (Notice that the log OR in an a vs. c table is infinite whichever way you turn it.) The likelihood ratio test (as in drop1(m1, test="Chisq")) is somewhat less unreliable, but in these small examples, still quite some distance from the table based approaches of fisher.test(a,c) and chisq.test(a,c). > > I hope that this message is understandable. > > Kind regards, Søren > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907 ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
