Regression models for count data based on the negative binomial(p) distribution
James W. Hardin
Institute for Families in Society
Department of Epidemiology and Biostatistics
University of South Carolina
Columbia, SC
[email protected]
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Joseph M. Hilbe
School of Social and Family Dynamics
Arizona State University
Tempe, AZ
[email protected]
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Abstract. We present new Stata commands for estimating several regression
models suitable for analyzing overdispersed count outcomes. The nbregp command
nests the dispersion(constant) and dispersion(mean) versions of Stata’s nbreg
command in a model for negative binomial(p) regression. The zignbreg command
extends Stata’s gnbreg command for zero inflation, and the zinbregp command fits
a negative binomial(p) regression model with zero inflation. The new commands
for zero-inflated models allow specification of links within the glm command’s
collection for the Bernoulli model of zero inflation. These commands will optionally
calculate a Vuong test, which compares the zero-inflated model with the nonzeroinflated
model.
View all articles by these authors:
James W. Hardin, Joseph M. Hilbe
View all articles with these keywords:
nbregp, zignbreg, zinbregp, Vuong test, zero inflation
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