Dispersion in summary.glm() with binomial & poisson link (fwd)

But GLIM and S and R will in their own ways fit those models, and
I want to look hard to see if what they do in R is sensible (and
some things seem not to be, as Ben Bolker pointed out ca April 19).

Thanks: I've been following this discussion with interest, since I had
wondered if my previous message had disappeared into the void ... I'm
getting lots of the information I wanted from this exchange.

   While we're on the topic: would it make any sense in this context to
implement the F-test suggested in MASS3 p. 215 (eq 7.10), or does the fact
that "this must be used with some caution in non-Gaussian cases" suggest
that it would be better to leave it out and not let people get into
trouble using it?

  Should the documentation about scale parameters say that if you're
heavily into estimating scale parameters you should probably be using
quasi-likelihoods instead?

  Just out of curiosity, is there documentation for profile.glm beyond
what's in MASS3?  (Or should it just be linked/added to the profile.nls
help?)  (I'm thinking about writing a profile.ms or something like that;
I've been having my students look at likelihood profiles a lot.)

  I will look into Jim Lindsey's code (which sounds like it does specific
extensions of binomial/Poisson rather than quasi-likelihood?)

 thanks all,
    Ben

Ben Bolker                                  bolker at zoo.ufl.edu
Zoology Department, University of Florida   http://www.zoo.ufl.edu/bolker
318 Carr Hall/Box 118525                    tel: (352) 392-5697
Gainesville, FL 32611-8525                  fax: (352) 392-3704

-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._