Maximum likelihood estimation and testing of a poisson regression model.

Jim Wan, A. T. Galecki

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)215-218
Number of pages4
JournalMethods of Information in Medicine
Volume31
Issue number3
StatePublished - Sep 1 1992
Externally publishedYes

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Likelihood Functions
Incidence

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Advanced and Specialized Nursing
  • Health Information Management

Cite this

Maximum likelihood estimation and testing of a poisson regression model. / Wan, Jim; Galecki, A. T.

In: Methods of Information in Medicine, Vol. 31, No. 3, 01.09.1992, p. 215-218.

Research output: Contribution to journalArticle

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