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Selection of Working Correlation Structure in Weighted Generalized Estimating Equation Method for Incomplete Longitudinal Data

机译:不完全纵向数据加权广义估计方程法中工作相关结构的选择

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The weighted generalized estimating equation (WGEE), an extension of the generalized estimating equation (GEE) method, is a method for analyzing incomplete longitudinal data. An inappropriate specification of the working correlation structure results in the loss of efficiency of the GEE estimation. In this study, we evaluated the efficiency of WGEE estimation for incomplete longitudinal data when the working correlation structure was misspecified. As a result, we found that the efficiency of the WGEE estimation was lower when an improper working correlation structure was selected, similar to the case of the GEE method. Furthermore, we modified the criterion proposed by Gosho et al. (2011) for selecting a working correlation structure, such that the GEE and WGEE methods can be applied to incomplete longitudinal data, and we investigated the performance of the modified criterion. The results revealed that when the modified criterion was adopted, the proportion that the true correlation structure was selected was likely higher than that in the case of adopting other competing approaches.
机译:加权广义估计方程(WGEE)是广义估计方程(GEE)方法的扩展,是一种分析不完整纵向数据的方法。工作相关性结构的不适当规范会导致GEE估计效率的损失。在这项研究中,当工作相关结构指定不正确时,我们评估了WGEE估计对于不完整的纵向数据的效率。结果,我们发现,当选择了不正确的工作相关结构时,WGEE估计的效率较低,类似于GEE方法的情况。此外,我们修改了Gosho等人提出的标准。 (2011年)选择一个工作相关结构,以便可以将GEE和WGEE方法应用于不完整的纵向数据,我们研究了修改后的准则的性能。结果表明,采用修正标准时,选择真实相关结构的比例可能比采用其他竞争方法时更高。

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