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