From: John Maindonald <john.maindonald_at_anu.edu.au>

Date: Fri 12 Jan 2007 - 21:48:06 GMT

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sat Jan 13 09:05:54 2007

Date: Fri 12 Jan 2007 - 21:48:06 GMT

On 12 Jan 2007, at 10:00 PM, r-help-request@stat.math.ethz.ch wrote:

> From: Peter Dalgaard <p.dalgaard@biostat.ku.dk>

*> Date: 12 January 2007 5:04:26 AM
**> To: evaiannario <evaiannario@libero.it>
**> Cc: "r-help@stat.math.ethz.ch" <r-help@stat.math.ethz.ch>
**> Subject: Re: [R] overdispersion
**>
**>
**> evaiannario wrote:
**>> How can I eliminate the overdispersion for binary data apart the
**>> use of the quasibinomial?
**> There is no such thing as overdispersion for binary data. (The
**> variance of a two-point distribution is a known function of the
**> mean.) If what you want to do is include random effects of some
**> sort of grouping then you might look into generalized linear mixed
**> models via lmer() from the lme4 package or glmmPQL from MASS.
*

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sat Jan 13 09:05:54 2007

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