Fixed Effects Regression Methods for Longitudinal Data Using SAS

4.1. Introduction

Many response variables are counts of something: number of articles published by scientists, number of sex partners in the last year, number of arrests in a one-year period, number of students enrolled in a class, and so on. Some data analysts still treat count variables as continuous measures and apply ordinary linear regression. But that practice ignores two facts: the data are really discrete, and the distributions of count variables are typically highly skewed. For these reasons, it may be inappropriate to use models that assume normally distributed errors.

Nowadays, it's becoming increasingly popular to estimate Poisson regression models or negative binomial regression models, both of which are explicitly designed to model ...