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
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