Check out these recent postings to the R list:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48429.html
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48646.html
Cheers, Pierre
[EMAIL PROTECTED] wrote:
Greetings R Users!
I have a data set of count responses for which I have made repeated observations on the experimental units (stream reaches) over two air photo dates, hence the mixed effect. I have been using Dr. Jim Lindsey's GLMM function found in his "repeated" measures package with the "poisson" family.
My problem though is that I don't think the poisson distribution is the right one to discribe my data which is overdispersed; the variance is greater than the mean. I have read that the "negative binomial" regression models can account for some of the differences among observations by adding in a error term that independent of the the covariates.
I haven't yet come across a mixed effects model that can use the "negative binomial" distribution.
If any of you know of such a function - I will certainly look forward to hearing from you! Additionally, if any of you have insight on zero-inflated data, and testing for this, I'd be interested in your comments too. I'll post a summary of your responses to this list.
Best Regards, Nadele Flynn, M.Sc. candidate. University of Alberta
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-- ----------------------------------------------------------------- Pierre Kleiber, Ph.D Email: [EMAIL PROTECTED] Fishery Biologist Tel: 808 983-5399 / (hm)808 737-7544 NOAA Fisheries Service - Honolulu Laboratory Fax: 808 983-2902 2570 Dole St., Honolulu, HI 96822-2396 ----------------------------------------------------------------- "God could have told Moses about galaxies and mitochondria and all. But behold... It was good enough for government work."
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