"Martin Henry H. Stevens" <[EMAIL PROTECTED]> writes: > Hello all: > I frequently have glm models in which the residual variance is much > lower than the residual degrees of freedom (e.g. Res.Dev=30.5, Res.DF > = 82). Is it appropriate for me to use a quasipoisson error > distribution and test it with an F distribution? It seems to me that > I could stand to gain a much-reduced standard error if I let the > procedure estimate my dispersion factor (which is what I assume the > quasi- distributions do). > > Thank you for any input at all.
I don't think it is safe to say anything general about this without knowledge of the model and the subject matter. Residual deviances can be terribly misleading. Consider for instance this: y <- c(0,1); w <- c(50,50) summary(glm(y~1, binomial, weights=w)) y1 <- .5; w1 <- 100 summary(glm(y1~1, binomial, weights=w1)) Notice that coeff. and s.e. is exactly the same, but not the residual deviances. Now, in the first case, did the zeros and ones sort themselves into two completely separated groups, or was that just because data was given pre-tabulated? -- 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 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
