[R] glm and overdispersion

[Ben Bolker]

  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 Loïc 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
> 

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