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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