Overdispersion and Poisson Regression

This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion. Some go on to assert that th...

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Detalles Bibliográficos
Autores principales: Berk, Richard (Autor) ; MacDonald, John M. (Autor)
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2008
En: Journal of quantitative criminology
Año: 2008, Volumen: 24, Número: 3, Páginas: 269-284
Acceso en línea: Volltext (lizenzpflichtig)
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Palabras clave:
Overdispersion
Count data
Negative binomial distribution
Poisson regression
Descripción
Sumario:This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion. Some go on to assert that the overdisperson problem can be “solved” when the negative binomial distribution is used instead of the more conventional Poisson distribution. In this paper, we review the assumptions required for both distributions and show that only under very special circumstances are these claims true.
ISSN:1573-7799
DOI:10.1007/s10940-008-9048-4