Maximum Likelihood Estimation and Testing of a Poisson Regression Model

J. Y. Wan; A. T. Galecki

doi:10.1055/s-0038-1634875

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1992; 31(03): 215-218
DOI: 10.1055/s-0038-1634875

Original Article

Schattauer GmbH

Maximum Likelihood Estimation and Testing of a Poisson Regression Model

J. Y. Wan

¹Departments of Biostatistics and Geriatric Research and Training Center

,

A. T. Galecki

²University of Michigan, Ann Arbor, Michigan, USA

› Author Affiliations

Abstract

Abstract:

A Poisson regression model is proposed for the analysis of incidence rates presented in a two-way table classified by two categorical variables. It is shown that the likelihood function is the same as that using Glasser’s exponential covariate model. An algorithm is given to solve the maximum likelihood estimates of the regression parameters. The model is evaluated via deviance and the method is illustrated with an example. Some extensions of the model are discussed.

Key-Words

Deviance - Exponential Regression - Incidence Rate - Poisson Regression

Full Text

References

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