Fitting a mixed negative binomial model
I *think* (but am not sure) that these guys were actually (politely)
advertising a commercial package that they're developing. But, looking at
the web page, it seems that this module may be freely available -- can't
tell at the moment.
Ben
On Wed, 13 Apr 2005, Henric Nilsson wrote:
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
620B Bartram Hall bolker at zoo.ufl.edu Zoology Department, University of Florida http://www.zoo.ufl.edu/bolker Box 118525 (ph) 352-392-5697 Gainesville, FL 32611-8525 (fax) 352-392-3704