[R] glm questions

[Thomas Lumley]

On Tue, 16 Mar 2004, David Firth wrote:

> I am unclear what you are asking here.  I assume by "scaled deviance"
> you mean deviance divided by phi, a (known) scale parameter?  (I'm
> sorry, I don't know SAS's definition.)    In many applications (eg
> binomial, Poisson) deviance and scaled deviance are the same thing,
> since phi is 1.  Yes, if you wanted to judge overdispersion relative to
> some other value of phi you would scale the deviance.  What other value
> of phi would you like?

For the quasibinomial() and quasipoisson() families you do get a scale
parameter estimate, computed from the variance of the Pearson residuals.

>
> On Tuesday, Mar 16, 2004, at 06:00 Europe/London, Paul Johnson wrote:
> >
> > 4. For GLM teaching purposes, can anybody point me at some good
> > examples of GLM that do not use Normal, Poisson, Negative Binomial,
> > and/or Logistic Regression?  I want to justify the effort to
> > understand the GLM as a framework.  We have already in previous
> > semesters followed the usual "econometric" approach in which OLS,
> > Poisson/Count, and Logistic regression are treated as special cases.
> > Some of the students don't see any benefit from tackling the GLM's new
> > notation/terminology.
>

David pointed out the Gamma models (both log link and reciprocal link). I
like the binomial with log link, which gives relative risks rather than
odds ratios.  These give examples where you might want two different link
functions for the same variance function.  There's also a paper by Nelder
in Applied Statistics (1994) talking about power link and variance for
skewed non-negative data.

	-thomas