Estimating the Relative Risk with Censored Data
研究了删失数据下两样本比例风险模型中相对风险的非参数估计量，推导了其渐近分布，并发现该类中的最优估计量与Cox最大偏似然估计具有相同的性质。
Abstract We investigate a class of nonparametric estimators of relative risk in the two-sample case of the proportional hazards model for censored data. The asymptotic distribution of these estimators is derived using influence functions. The optimal estimator in this class has the same influence functions and the same asymptotic distribution as the maximum partial likelihood estimator of Cox (1972). The behavior of the influence functions is discussed briefly, and the last section presents two examples from the literature.