Generalized Binomial Regression Model

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Abstract

The generalized negative binomial distribution has been found useful in fitting over‐dispersed as well as under‐dispersed count data. We define and study the generalized binomial regression model which is used to predict a count response variable affected by one or more explanatory variables. The methods of maximum likelihood and moments are given for estimating the model parameters. Approximate tests for the adequacy of the model are considered. The generalized binomial regression model has been applied to two observed data sets to which binomial regression model was applied earlier.

Original languageEnglish
Pages (from-to)581-594
Number of pages14
JournalBiometrical Journal
Volume37
Issue number5
DOIs
StatePublished - 1995

Keywords

  • Carrot fly larvae distribution
  • Deviance
  • Dose‐response
  • Over‐dispersion
  • Parameter estimation
  • Under‐dispersion

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