Generalised linear models II: Poisson regression

  • Brian Everitt
  • Sophia Rabe-Hesketh
Part of the Statistics for Biology and Health book series (SBH)

Abstract

In the previous chapter, we used logistic regression to model binary variables and proportions. In this chapter, we will use another type of generalized linear model, Poisson regression, to model counts. Many medical and epidemiological investigations are concerned with the incidence of diseases in populations. Here, a number of people are followed up and the onset of a disease recorded for each person. The data can then be summarized by counting the total number of occurrences of the disease in different subgroups of subjects sharing the same values of the important explanatory variables. The dependent variable is therefore a count.

Keywords

Poisson Regression Dispersion Parameter Incidence Rate Ratio Deviance Residual Expected Count 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Brian Everitt
    • 1
  • Sophia Rabe-Hesketh
    • 1
  1. 1.Biostatistics and Computing DepartmentInstitute of PsychiatryLondonUK

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