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
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