[R] Dispersion in summary.glm() with binomial & poisson link

[Prof Brian D Ripley]

On Tue, 9 May 2000, John Maindonald wrote:

> > From ripley at stats.ox.ac.uk  Tue May  9 15:30:33 2000
> > Date: Tue, 9 May 2000 06:29:10 +0100 (BST)
> 
> > > Following p.206 of "Statistical Models in S", I wish to change
> > > the code for summary.glm() so that it estimates the dispersion
> > > for binomial & poisson models when the parameter dispersion is
> > > set to zero.  The following changes [insertion of ||dispersion==0
> > > at one point; and !is.null(dispersion) at another] will do the trick:
> > 
> > I know S does that, but R is not documented to do so (so your example does
> > works as documented).  I think this is at best confusing. Once phi is
> > estimated, they are quasi-likelihood models not binomial nor Poisson and in
> > particular have no likelihood, so e.g. drop1 becomes inappropriate.  And it
> > is all too easy to have different treatments of dispersion in different
> > ancilliary functions (as S managed for many years).
> 
> That is why I did not submit a bug report.  The problem is that in
> many application areas phi is much greater than one.
> 
> > My preference is to treat such models as quasi models.  If enough
> > people really want them as `binomial' or `poisson' then we need to
> > make much wider changes to ensure consistency (and incompitibility
> > with S).
> 
> I agree with the sentiments.  So would it be feasible to have
> quasi-poisson and quasi-binomial errors?  Would an immediate recourse
> be to create functions summary.quasi and predict.quasi?  Or perhaps
> summary.phi, etc.

All you need is a function to estimate dispersion as you want
(and there are other ways for gammas, e.g. in the MASS library).
So you call, e.g.

summary(object, dispersion=chisquare.dispersion(object))

but a simpler interface is desirable, and yes, quasibinomial and
quasipoisson look an excellent idea.

Because I was aware of the (in)consistency issues I am looking into this.
Expect something along these lines for 1.1.x.

(BTW, now is a good time to raise such design issues. As you will see from
http://developer.r-project.org 1.1 is about a month off, and our plans are
for 1.1.1 to be the version for teaching in academic year 2000/1 in Europe
and N. America.)

Brian

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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