Censored Median Regression Using Weighted Empirical Survival and Hazard Functions
针对生存时间可能被删失的中位数回归模型，提出了不依赖删失分布估计的半参数估计量，基于加权经验生存和风险函数，具有一致性和渐近正态性，在数值研究和实际数据中表现良好。
Abstract For median regression models that regress the median of the survival time or a transform thereof on the covariates, some semi-parametric estimators that include the intercept component are introduced when the survival time may be censored. These new median regression estimators do not require estimating the censoring distributions. They can be viewed as an extension of the sample median to the censored regression model. These estimators are based on some weighted empirical survival and hazard functions and are shown to be consistent and asymptotically normal. They performed very well in various numerical studies. The proposed procedures are illustrated in some real data examples.