Zero-inflated negative binomial mixed model?
Roberto-- Yau et al. wrote some functions in Splus to fit their models. At one point, I had gotten them (I think from Andy Lee, if memory serves), though they are not terribly user-friendly, and I think the last time I tried to use them in R (a couple years back), I was unable to do so. However, I would definitely recommend the MCMCglmm package, which can fit an over-dispersed Poisson mixed model. It includes a per-observation random-effect to handle the over-dispersion. Hope that helps. cheers, Dave
Roberto wrote:
Dear Listers, I was wondering if there is any implementation available in R of a GLMM based on a zero-inflated negative binomial (basically a zero-inflated negative binomial mixed effects model). I see at least one paper online (KKW Yau, K Wang, AH Lee - Biometrical Journal, 2003) where something like this has been developed (but right now I can't read the paper because Wiley Interscience is down for maintenance). Thanks and best regards, Roberto Patuelli ******************** Roberto Patuelli, Ph.D. Istituto Ricerche Economiche (IRE) (Institute for Economic Research) Universit? della Svizzera Italiana (University of Lugano) via Maderno 24, CP 4361 CH-6904 Lugano Switzerland Phone: +41-(0)58-666-4166 Fax: +39-02-700419665 Email: roberto.patuelli at usi.ch Homepage: http://www.people.lu.unisi.ch/patuellr
Dave Atkins, PhD Research Associate Professor Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu Center for the Study of Health and Risk Behaviors (CSHRB) 1100 NE 45th Street, Suite 300 Seattle, WA 98105 206-616-3879 http://depts.washington.edu/cshrb/ (Mon-Wed) Center for Healthcare Improvement, for Addictions, Mental Illness, Medically Vulnerable Populations (CHAMMP) 325 9th Avenue, 2HH-15 Box 359911 Seattle, WA 98104? 206-897-4210 http://www.chammp.org (Thurs)