title: Statistical analysis of correlated data using generalized estimating equations: an orientation.
abstract: The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciate the essence of the method. The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data.
authors.affiliation: Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada. james.hanley@mcgill.ca
authors.forename: James A
authors.initials: JA
authors.lastname: Hanley
authors.forename: Abdissa
authors.initials: A
authors.lastname: Negassa
authors.forename: Michael D deB
authors.initials: MD
authors.lastname: Edwardes
authors.forename: Janet E
authors.initials: JE
authors.lastname: Forrester
mesh_terms: D001827:Body Height; D002648:Child; D004812:Epidemiologic Methods; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D012959:Socioeconomic Factors