Models for Longitudinal Data: A Generalized Estimating Equation Approach
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ID: 289596
1988
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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.
| Reference Key |
openalex_W1976566530
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|---|---|
| Authors | Scott L. Zeger, Kung‐Yee Liang, Paul S. Albert |
| Journal | biometrics |
| Year | 1988 |
| DOI |
10.2307/2531734
|
| URL | |
| Keywords | Keywords not found |
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