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Estimated Generalized Estimating Equation for Correlated Failure Time Data with Auxiliary Covariates

机译:辅助协变量相关故障时间数据的估计估计估计方程

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In this article, we study a marginal hazard model with common baseline hazard for correlated failure time data. We assume that the true covariate is measured precisely in a subset of the whole study cohort, whereas an auxiliary information for the true covariate is available for the whole cohort. We first estimate the relative risk function empirically. Then we obtain the estimator for the regression parameter by replacing the relative risk function with its estimator in a generalized estimating equation (GEE) proposed by Cai (1992). A key feature of this method is that it is nonparametric with respect to the association between the missing covariate and the observed auxiliary covariate. The proposed estimator is shown to be consistent and asymptotically normal. Furthermore, we present a corrected Breslow-type estimator for the cumulative hazard function. Simulation studies are conducted to evaluate the proposed method.
机译:在本文中,我们研究了具有常见基线危害的边际危险模型,用于相关的故障时间数据。我们假设真正的协变量是精确地测量整个研究队列的子集,而真正的协变量的辅助信息可用于整个队列。我们首先估计经验上的相对风险功能。然后,通过在CAI(1992)提出的广义估计方程(GEE)中,通过将相对风险功能替换相对风险函数来获得回归参数的估计器。该方法的一个关键特征是它对于缺失的协变量和观察到的辅助协变量之间的关联是非参数。所提出的估算器被证明是一致的和渐近正常的。此外,我们为累积危险功能提出了校正的Brieslow型估计器。进行仿真研究以评估所提出的方法。

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