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A practical extension of the generalized estimating equation approach for longitudinal data. (English) Zbl 0875.62340

Summary: Liang and Zeger (1986) proposed an extension of generalized linear models to the analysis of longitudinal data. In their formulation, a common dispersion parameter assumption across observation times is required. However, this assumption is not expected to hold in most situations. T. Park [Statistics in Medicine 12, 1723-1732 (1993)]proposed a simple extension of Liang and Zeger’s formulation to allow for different dispersion parameters for each time point. The proposed model is easy to apply without heavy computations and useful to handle the cases when variations in over-dispersion over time exist. In this paper, we focus on evaluating the effect of additional dispersion parameters on the estimators of model parameters. Through a Monte Carlo simulation study, efficiency of Park’s method is compared with Liang and Zeger’s method.

MSC:

62J12 Generalized linear models (logistic models)
62F10 Point estimation
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