Use family=quasibinomial in your glm() statement. R "does what you say rather than doing what you mean": it specifically says something like "(Dispersion for binomial family taken to be 1)", which is an indication that R is not using a dispersion factor > 1 in this case. (There is a hint of this in the ?anova.glm man page: "For models with known dispersion (e.g. binomial and Poisson fits) the chi-squared test is most appropriate, and for those with dispersion estimated by moments (e.g. `gaussian', `quasibinomial' and `quasipoisson' fits) the F test is most appropriate.")
I brought this up with R-devel -- I think that many people are likely to run into this confusion -- but I wasn't sufficiently convincing to get a note put into the help page ... Ben On Tue, 18 Feb 2003, Hardouin Lo�c wrote: > > Hi, > > I am performing glm with binomial family and my data show slight > overdispersion (HF<1.5). Nevertheless, in order to take into account for > this heterogeneity though weak, I use F-test rather than Chi-square > (Krackow & Tkadlec, 2001). But surprisingly, outputs of this two tests > are exactly similar. What is the reason and how can I scale the output > by overdispersion ?? > > Thank you, > > Alexandre MILLON > -- 318 Carr Hall [EMAIL PROTECTED] Zoology Department, University of Florida http://www.zoo.ufl.edu/bolker Box 118525 (ph) 352-392-5697 Gainesville, FL 32611-8525 (fax) 352-392-3704 ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
