Essential Statistics Using SAS University Edition

Chapter 8: Poisson Regression and the Generalized Linear Model

8.1 Introduction

8.2 Generalized Linear Model

8.2.1 Components of Generalized Linear Models

8.2.2 Using the Generalized Linear Model to Apply Multiple Linear Regression and Logistic Regression

8.3 Poisson Regression

8.3.1 Example 1: Familial Adenomatous Polyposis (FAP)

8.3.2 Example 2: Bladder Cancer

8.4 Overdispersion

8.5 Summary

8.6 Exercises

8.1 Introduction

In this chapter, we show how the multiple linear regression model and the logistic regression model can both be subsumed within a more general modelling framework, the generalized linear model (GLM), and how the GLM then leads to more appropriate models for response variables that cannot (and should not) be modelled by the ...