Under-dispersion - a stats question?

"Martin Henry H. Stevens" <HStevens at muohio.edu> 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?

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