[R] overdispersion + GAM

[Ravi Varadhan]

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.

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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

 

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-----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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