论文标题
通过审查和协变量减小的平均残留寿命的半参数回归
Semiparametric regression of mean residual life with censoring and covariate dimension reduction
论文作者
论文摘要
我们提出了一类新的半参数回归模型，以审查结果数据的平均残留寿命。这些模型使我们能够估算预期的剩余生存时间并概括常用的平均剩余生命模型，还进行了协变量降低。使用半乳头文献中的几何方法和具有生存数据的Martingale特性，我们提出了一种灵活的推理程序，可以放松对平均残留寿命对协变量的依赖性以及患者的寿命的参数假设。我们表明，协变量效应的估计量是root-$ n $一致的，渐近正常和半绘制效率的。通过未指定的平均残留寿命函数，我们提供了一个非参数估计量来预测给定受试者的剩余寿命，并为该估计器建立根 - $ n $的一致性和渐近态性。进行数值实验以说明所提出的估计器的可行性。我们应用了分析国家肾脏移植数据集的方法，以进一步证明工作的实用性。
We propose a new class of semiparametric regression models of mean residual life for censored outcome data. The models, which enable us to estimate the expected remaining survival time and generalize commonly used mean residual life models, also conduct covariate dimension reduction. Using the geometric approaches in semiparametrics literature and the martingale properties with survival data, we propose a flexible inference procedure that relaxes the parametric assumptions on the dependence of mean residual life on covariates and how long a patient has lived. We show that the estimators for the covariate effects are root-$n$ consistent, asymptotically normal, and semiparametrically efficient. With the unspecified mean residual life function, we provide a nonparametric estimator for predicting the residual life of a given subject, and establish the root-$n$ consistency and asymptotic normality for this estimator. Numerical experiments are conducted to illustrate the feasibility of the proposed estimators. We apply the method to analyze a national kidney transplantation dataset to further demonstrate the utility of the work.
