失效信息随机缺失时可加危险率模型的统计推断

Statistic inference of additive hazards model when censoring indicators are missing at random

对失效信息随机缺失时的可加危险率模型的估计进行研究.充分利用失效信息和缺失信息的概率模型的信息,通过构建估计方程,得到回归参数和基准累积风险函数的3个估计.证明了所提估计的渐近正态性,并进行数值模拟研究其有限样本性质.利用数值模拟研究比较所提估计与文献中的估计的有限样本性质,并通过分析一个实际数据验证了本文方法的有效性.

In this work,we consider a semi-parametric additive hazards regression model for rightcensored data with censoring indicators missing at random. By employing the information of the response and censoring probability models,we propose three estimators of the regression coefficient and the baseline cumulative hazard function. We prove that the proposed estimators are consistent and asymptotically normal. Simulation studies are conducted to evaluate the numerical performance of the proposed estimators in comparison with the existing estimators. A real data set is analyzed to validate the effectiveness of the proposed methods.