title: Alternative approaches to the analysis of binary and categorical repeated measurements.
abstract: 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.
authors.affiliation: Department of Applied Statistics, University of Reading, England.
authors.forename: M G
authors.initials: MG
authors.lastname: Kenward
authors.forename: B
authors.initials: B
authors.lastname: Jones
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D012107:Research Design / Q000706:statistics & numerical data*