Message-ID: <425D4784.6080404@statisticon.se>
Date: 2005-04-13T16:23:32Z
From: Henric Nilsson
Subject: Fitting a mixed negative binomial model
In-Reply-To: <Pine.LNX.4.62.0504121536450.26563@bolker.zoo.ufl.edu>
Ben Bolker said the following on 2005-04-12 21:40:
> This is a little bit tricky (nonlinear, mixed, count data ...) Off the
> top of my head, without even looking at the documentation, I think your
> best bet for this problem would be to use the weights statement to allow
> the variance to be proportional to the mean (and add a normal error term
> for individuals) -- this would be close to equivalent to the log-Poisson
> model used by Elston et al. (Parasitology 2001, 122, 563-569, "Analysis
> of aggregation, a worked example: numbers of ticks on red grouse
> chicks"), and might do what you want.
A recent posting
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48429.html
suggests that an R function for fitting the negative binomial
mixed-effects model actually exists.
HTH,
Henric