Models for Longitudinal Data: A Generalized Estimating Equation Approach

Biometrics. 1988 Dec;44(4):1049-60.

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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Child
  • Humans
  • Longitudinal Studies*
  • Models, Statistical*
  • Mothers
  • Regression Analysis
  • Respiratory Tract Infections / epidemiology
  • Smoking