From bbolker at gmail.com  Thu Jun 25 17:25:37 2015
From: bbolker at gmail.com (Ben Bolker)
Date: Thu, 25 Jun 2015 15:25:37 +0000
Subject: [Rd]
	=?utf-8?q?Estimating_overdispersion_when_using_glm_for_count?=
	=?utf-8?q?_and=09binomial_data?=
References: <124680c8e766db6e1fc34a92cab86079@maths.otago.ac.nz>
Message-ID: <loom.20150625T172018-212@post.gmane.org>

David Fletcher <dfletcher <at> maths.otago.ac.nz> writes:

> 
> Dear All
> 
> I recently proposed a simple modification to Wedderburn's 1974 estimate 
> of overdispersion for count and binomial data, which is used in glm for 
> the quasipoisson and quasibinomial families (see the reference below).
> 

 [snip]

> 
> The modification is very simple and would take at most a couple of 
> lines of code. The reference below gives details regarding its 
> asymptotic properties, as well as simulation results that illustrate the 
> benefits of using it for sparse data.
> 
  [snip]

> 
> D.J. Fletcher (2012) Estimating overdispersion when fitting a 
> generalized linear model to sparse data. Biometrika 99:230?237 
> (http://biomet.oxfordjournals.org/content/99/1/230.abstract?etoc)

  This looks really useful.  Base R is very conservative; despite the
fact that it would be much more easily adopted in base R, I think it
is much more likely to find a home in an add-on package such as aods3
or glm2 than in base R ...

  cheers
    Ben Bolker

  


[Rd] =?utf-8?q?Estimating_overdispersion_when_using_glm_for_count?= =?utf-8?q?_and=09binomial_data?=
Ben Bolker