Re: lme for count data?

["A&B Penner" <pennerab@gmail.com>]

Thank you to everyone who replied to my question: I will use the glme() function from the correlatedData library to perform a mixed-effects model on my count data.

This brings up a new question. Is there a way to compare overall glme model fits when the models have different fixed-effect terms? For example, lme models estimated by maximum likelihood can be compared using a drop-in-deviance test performed by the anova function.  Is there anything similar for glme models?

Additionally, besides Venables and Ripley 2002 and the help file for the correlatedData library, are there other basic references for performing and interpreting generalized linear mixed models?

Many thanks,
A. Penner

On 10/29/07, Michael O'Connell <moconnell@insightful.com> wrote:

yes, the correlatedData library and associated glme() function postdate the Pinheiro and Bates text.

 

gee() in the correlatedData library will also work for these data. I prefer the glme() implementation in this case.

 

Michael

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From: s-news-owner@lists.biostat.wustl.edu [mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of Austin, Matt
Sent: Thursday, October 25, 2007 8:14 PM
To: A&B Penner; s-news@lists.biostat.wustl.edu
Subject: Re: [S] lme for count data?

In the past I would have suggested looking at glmmPQL() in the MASS library or glme() in the correlatedData library if you have grouped count data, but I can't find the correlatedData library in version 8.

 

Another alternative would be a GEE approach.

 

The MASS text by Venables and Ripley gives a short overview of both methods (PQL and GEE) and good references for deeper study.  It also gives a brief explanation of the difference in interpretation between the methods.  I believe the correlatedData library and associated glme() function postdate the Pinheiro and Bates text.

 

 

--Matt

 

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From: s-news-owner@lists.biostat.wustl.edu [mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of A&B Penner
Sent: Thursday, October 25, 2007 1:50 PM
To: s-news@lists.biostat.wustl.edu
Subject: [S] lme for count data?

 

Hi,

I'd like to fit a mixed-effects model to my data. Pinheiro and Bates (2000) write that "These models are intended for grouped data in which the response variable is (at least approximately) continuous." My response variable is count data with range from 0-4, mean 1.7, median 2.0, stdev 0.8, and an approximately normal distribution. Can I use the lme function for this data?

Thank you,
A. Penner