Apparant bug in binomial model in GLM (PR#13434)
soren.faurby at biology.au.dk wrote:
Full_Name: S?ren 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, S?ren
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O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907