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Dear Lister, I am facing a strange problem fitting a GLM of the negative binomial family. Actually, I tried to estimate theta (the scale parameter) through glm.nb from MASS and could get convergence only relaxing the convergence tolerance to 1e-3. With warning messages: glm1<-glm.nb(nbcas~.,data=zonesdb4,control=glm.control(epsilon = 1e-3)) There were 25 warnings (use warnings() to see

Hi, I have some data on the effect of cycle shape (categorical) and frequency (continuous) on the efficiency of muscle contraction. My minimum adequate model is: m15<-glm(efficiency~cycle.shape*freq, family=quasipoisson) However, I wish to know where significant differences lie between specific combinations of treatments. I guess I want an equivalent of a post hoc test following an