具有Cox强度过程的多状态生存分析模型的自助法(英文)

Bootstrapping Cox's Regression Model with Time-dependent Covariates

本文利用计数过程技术及VonMises方法，研究了具有时变伴变量的删失生存资料的Cox回归模型的自助法的大样本性质．研究表明：在一些正则条件下，对这个模型施实自助法是可行的．即回归系数的偏极大似然估计及基准危险率的非参数极大似然估计的自过程是相合的．

Utilizing the counting process technology and the von Mises method, we discuss the asymptotic properties of bootstrapping the Cox’s regression model for censored survival data with time-dependent covariates which have a proportional effect on the hazard function of the life-time distribution of an individual. Under some regular assumptions, we show that bootstrapping the model is feasible: both the maximum partial likelihood estimators for the regression coefficients and the nonparametric estimator for the baseline cumulate hazard rate function is consistent.