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Overdispersion and Poisson Regression
by
MacDonald, John M.
, Berk, Richard
in
Binomial distributions
/ Binomials
/ Criminology
/ Criminology and Criminal Justice
/ Distribution
/ Expected values
/ Law and Criminology
/ Linear regression
/ Methodology of the Social Sciences
/ Original Paper
/ Poisson distribution
/ Poisson process
/ Regression analysis
/ Regression coefficients
/ Sociology
/ Statistical variance
/ Statistics
/ Stochastic models
2008
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Overdispersion and Poisson Regression
by
MacDonald, John M.
, Berk, Richard
in
Binomial distributions
/ Binomials
/ Criminology
/ Criminology and Criminal Justice
/ Distribution
/ Expected values
/ Law and Criminology
/ Linear regression
/ Methodology of the Social Sciences
/ Original Paper
/ Poisson distribution
/ Poisson process
/ Regression analysis
/ Regression coefficients
/ Sociology
/ Statistical variance
/ Statistics
/ Stochastic models
2008
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Overdispersion and Poisson Regression
by
MacDonald, John M.
, Berk, Richard
in
Binomial distributions
/ Binomials
/ Criminology
/ Criminology and Criminal Justice
/ Distribution
/ Expected values
/ Law and Criminology
/ Linear regression
/ Methodology of the Social Sciences
/ Original Paper
/ Poisson distribution
/ Poisson process
/ Regression analysis
/ Regression coefficients
/ Sociology
/ Statistical variance
/ Statistics
/ Stochastic models
2008
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Journal Article
Overdispersion and Poisson Regression
2008
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Overview
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.
Publisher
Springer Science+Business Media,Springer US,Springer Nature B.V
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