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Models for Longitudinal Data: A Generalized Estimating Equation Approach
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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Cited by
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Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Prospective Study of the Association between Sleep-Disordered Breathing and Hypertension
Peppard, P. E., Young, T., Palta, M., & Skatrud, J. (2000) · New England Journal of Medicine · doi:10.1056/nejm200005113421901 · Cited by 4,973
Prevalence and development of psychiatric disorders in childhood and adolescence
Costello, E. J., Mustillo, S., Erkanli, A., Keeler, G., & Angold, A. (2003) · Archives of General Psychiatry · doi:10.1001/archpsyc.60.8.837 · Cited by 4,035
Metadata
- Authors
- Zeger, S. L., Liang, K.-Y., & Albert, P. S.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1988-12
- Volume
- 44
- Issue
- 4
- Pages
- 1049
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W1976566530
- Cited by
- 4,505
- References
- 0
- FWCI
- 13.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zeger, S. L., Liang, K.-Y., & Albert, P. S. (1988). Models for Longitudinal Data: A Generalized Estimating Equation Approach. Biometrics. https://doi.org/10.2307/2531734
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