Weighted estimating equation: modified GEE in longitudinal data analysis |
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Authors: | Tianqing Liu Zhidong Bai Baoxue Zhang |
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Institution: | 1. School of Mathematics, Jilin University, Changchun 130012, China2. Key Laboratory for Applied Statistics of MOE and School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China |
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Abstract: | The method of generalized estimating equations (GEE) introduced by K. Y. Liang and S. L. Zeger has been widely used to analyze longitudinal data. Recently, this method has been criticized for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. In this paper, we present a new method named as ‘weighted estimating equations (WEE)’ for estimating the correlation parameters. The new estimates of correlation parameters are obtained as the solutions of these weighted estimating equations. For some commonly assumed correlation structures, we show that there exists a unique feasible solution to these weighted estimating equations regardless the correlation structure is correctly specified or not. The new feasible estimates of correlation parameters are consistent when the working correlation structure is correctly specified. Simulation results suggest that the new method works well in finite samples. |
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Keywords: | Consistency correlation efficiency (GEE) longitudinal data positive definite estimating equation (WEE) generalized estimating equation repeated measures weighted |
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