Alternative approaches to the analysis of binary and categorical repeated measurements

The purpose of this paper is to describe, illustrate, and compare a number of different approaches to the analysis of repeated binary and categorical data. These approaches include empirical generalized least squares and generalized estimating equations, as well as traditional log-linear modeling methods. It is shown that the interpretation of the parameters in the various models depends critically on the type of model fitted. In particular, we contrast the population-averaged and subject-specific models. Two example data sets are used to illustrate the approaches, and throughout we concentrate on methods that can be easily implemented.