Modeling underdispersed count data with generalized Poisson regression
Tammy Harris
Institute for Families in Society
Department of Epidemiology and Biostatistics
University of South Carolina
Columbia, SC
[email protected]
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Zhao Yang
Quintiles, Inc.
Morrisville, NC
[email protected]
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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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Abstract. We present motivation and new Stata commands for modeling count
data. While the focus of this article is on modeling data with underdispersion, the
new command for fitting generalized Poisson regression models is also suitable as
an alternative to negative binomial regression for overdispersed data.
View all articles by these authors:
Tammy Harris, Zhao Yang, James W. Hardin
View all articles with these keywords:
gpoisson, Poisson, count data, overdispersion, underdispersion
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