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      Models for longitudinal data: a generalized estimating equation approach.

      1 , ,
      Biometrics

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          Abstract

          This article discusses extensions of generalized linear models for the analysis of longitudinal data. Two approaches are considered: subject-specific (SS) models in which heterogeneity in regression parameters is explicitly modelled; and population-averaged (PA) models in which the aggregate response for the population is the focus. We use a generalized estimating equation approach to fit both classes of models for discrete and continuous outcomes. When the subject-specific parameters are assumed to follow a Gaussian distribution, simple relationships between the PA and SS parameters are available. The methods are illustrated with an analysis of data on mother's smoking and children's respiratory disease.

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          Author and article information

          Journal
          Biometrics
          Biometrics
          0006-341X
          0006-341X
          Dec 1988
          : 44
          : 4
          Affiliations
          [1 ] Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205.
          Article
          3233245
          bc2ecb25-c592-4e05-bbc9-cc91c0890689
          History

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