[R] Negative binomial regression for count data

From: Seyed Reza Jafarzadeh <srjafar_at_yahoo.com>
Date: Thu 03 Mar 2005 - 20:56:59 EST


Dear list,  

I would like to fit a negative binomial regression model as described in "Byers AL, Allore H, Gill TM, Peduzzi PN., Application of negative binomial modeling for discrete outcomes: a case study in aging research. J Clin Epidemiol. 2003 Jun;56(6):559-64" to my data in which the response is count data. There are also 10 predictors that are count data, and I have also 3 categorical and 2 continious predictors. There is overdispersion in the distribution of the response variable (mean=2.8, variance=28) as well as in predictors, and there are a lot of zero's (zero-inflated). The authors of that paper used PROC GENMOD in SAS 8.1. I wonder which of the following packages and tests to use in R to acheive such model for my analysis. Is there any tutorial available?  

anova.negbin

   Likelihood Ratio Tests for Negative Binomial GLMs glm.convert

   Change a Negative Binomial fit to a GLM fit glm.nb

   Fit a Negative Binomial Generalized Linear Model negative.binomial

   Family function for Negative Binomial GLMs rnegbin

   Simulate Negative Binomial Variates
theta.md

   Estimate theta of the Negative Binomial gam.neg.bin

   GAMs with the negative binomial distribution dnb2

   Density for negative binomial, used in mmlcr theta.mmmod

   Estimate theta of the Negative Binomial by Moments NegBinomial

   The Negative Binomial Distribution
ezinb

   The expected value of the censored zero-inflated negative binomial model  

Thanks,

Reza

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