Analysis of Correlation Structures using Generalized Estimating Equation Approach for Longitudinal Binary Data

Longitudinal binary data often arise in clinical trials when repeated measurements, positive or negative to certain tests, are made on the same subject over time. To account for the serial correlation within subjects, we propose a marginal logistic model which is implemented using the Generalized Estimating Equation (GEE) approach with working correlation matrices adopting some widely used forms. The aim of this paper is to seek some robust working correlation matrices that give consistently good it to the data. Model-it is assessed using the modified expected utility of Walker & Gutiérrez-Pe□a (1999). To evaluate the effect of the length of time series and the strength of serial correlation on the robustness of various working correlation matrices, the models are demonstrated using three data sets containing respectively all short time series, all long time series and time series of varying length. We identify factors that affect the choice of robust working correlation matrices and give suggestions under different situations.

並列關鍵字

Longitudinal data ； Serial correlation ； Robustness ； Generalized Estimating Equation approach

被引用紀錄

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國際替代計量

Analysis of Correlation Structures using Generalized Estimating Equation Approach for Longitudinal Binary Data

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