[R] glmmML vs. lmer - fitting overdispersed Poisson outcome.
fieldsh at mail.med.upenn.edu
Mon Oct 15 18:05:32 CEST 2007
I have count data with one observation per subject. I would like to fit
a glmm to these data in order to account for overdispersion in the
outcome. The lmer() function does not appear to be able to handle data
that have only one observation per-cluster id, even though separate
variance components for the count and normal portions of the outcome are
identifiable. The glmmML() function does not seem to have problems with
this (as the code below illustrates).
u <- rnorm(100)
y <- rpois(100,exp(u))
id <- seq(1:100)
I would like to use lmer() rather then glmmML(). Does anybody know of a
way of getting the lmer() function to work with these kinds of data?
Samuel H. Field
Division of Internal Medicine - University of Pennsylvania
CHERP - Philadelphia VA Medical Center
3900 Woodland Ave (9 East)
Philadelphia, PA 19104
(215) 823-5800 EXT. 6155 (Office)
(215) 823-6330 (Fax)
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