Re: [R] overdispersion + GAM

From: Ravi Varadhan <rvaradhan_at_jhmi.edu>
Date: Mon, 11 Feb 2008 14:46:50 -0500

No. Binomial data can indeed be overdispersed. See McCullagh & Nelder (1989, section 4.5). Accounting for over(under)dispersion in binomial and Poisson distributions is, in fact, one of the original impetus for GEE type developments. See also a nice paper by Liang & McCullagh (Biometrics 1993, p. 623-630), which discusses numerous examples of overdispersion in binary data.

Ravi.



Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan_at_jhmi.edu

Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html  



-----Original Message-----
From: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] On Behalf Of Gavin Simpson
Sent: Monday, February 11, 2008 12:37 PM To: anna banana
Cc: r-help_at_r-project.org
Subject: Re: [R] overdispersion + GAM

On Mon, 2008-02-11 at 07:35 -0800, anna banana wrote:
> Hi,
>
> there are a lot of messages dealing with overdispersion, but I couldn't
find
> anything about how to test for overdispersion. I applied a GAM with
binomial
> distribution on my presence/absence data, and would like to check for
> overdispersion. Does anyone know the command?

Bernoulli data (presence/absence of single species say) can't be overdispersed, so there is no need to test or correct for it.

G

>
> Many thanks,
>
> Anna

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