Efficiency of the Breslow estimator in semiparametric transformation models.
Efficiency of the Breslow estimator in semiparametric transformation models.
复制标题
半参数变换模型中 Breslow 估计器的效率。
DOI：
10.1007/s10985-023-09611-w
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发表时间：
2024
影响因子：
1.3
通讯作者：
Tsodikov,Alexander
中科院分区：
文献类型：
--
作者：
Devasia,TheresaP;Tsodikov,Alexander
故障时间数据的半参数转换模型由参数回归组件和未指定的累积基线危险组成。累积基线风险的非参数最大似然估计量（NPMLE）可根据引入Breslow型估计量（加权Breslow）的权重进行总结。在任何给定的时间点，权重调用累积基线危险的未来的积分，这提出了理论和计算挑战。一个更简单的非极大似然估计Breslow型估计量（Breslow）是从鞅估计方程（EFT）中推导出来的，该估计方程设置了观察到的失效次数和期望失效次数相等，条件是过去的历史。尽管有许多成功的理论和计算的发展，更简单的Breslow估计继续被普遍使用的简单性和感知损失的充分效率之间的妥协。在本文中，我们推导出的Breslow估计的相对效率，并考虑使用模拟和真实的数据对前列腺癌生存的两个估计的属性。
Semiparametric transformation models for failure time data consist of a parametric regression component and an unspecified cumulative baseline hazard. The nonparametric maximum likelihood estimator (NPMLE) of the cumulative baseline hazard can be summarized in terms of weights introduced into a Breslow-type estimator (Weighted Breslow). At any given time point, the weights invoke an integral over the future of the cumulative baseline hazard, which presents theoretical and computational challenges. A simpler non-MLE Breslow-type estimator (Breslow) was derived earlier from a martingale estimating equation (MEE) setting observed and expected counts of failures equal, conditional on the past history. Despite much successful theoretical and computational development, the simpler Breslow estimator continues to be commonly used as a compromise between simplicity and perceived loss of full efficiency. In this paper we derive the relative efficiency of the Breslow estimator and consider the properties of the two estimators using simulations and real data on prostate cancer survival.