[R-sig-ME] Zero-inflated negative binomial mixed model?

David Atkins datkins at u.washington.edu
Sat Jun 19 17:26:48 CEST 2010


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)
Università della Svizzera Italiana (University of Lugano)
via Maderno 24, CP 4361
CH-6904 Lugano
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

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