失效信息随机缺失时可加危险率模型的统计推断

doi:10.7523/j.issn.2095-6134.2016.04.003

中国科学院大学学报 ›› 2016, Vol. 33 ›› Issue (4): 443-453.DOI: 10.7523/j.issn.2095-6134.2016.04.003

失效信息随机缺失时可加危险率模型的统计推断

陈菲菲^1,2, 孙志华^1,2, 叶雪^1,2

1. 中国科学院大学数学科学学院, 北京 100049;
2. 中国科学院大数据挖掘与知识管理重点实验室, 北京 100190

收稿日期:2015-06-01 修回日期:2015-11-20 发布日期:2016-07-15
通讯作者: 孙志华
基金资助:
国家自然科学基金（10901162，U1430103，11571340）、中国科学院大学校长基金、中国科学院大数据挖掘与知识管理重点实验室开放课题和安徽省振兴计划团队项目（统计学前沿问题及应用）资助

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

CHEN Feifei^1,2, SUN Zhihua^1,2, YE Xue^1,2

1. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China;
2. Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China

Received:2015-06-01 Revised:2015-11-20 Published:2016-07-15

摘要/Abstract

摘要：

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。

关键词: 删失信息, 随机缺失, 可加危险率模型, 加权估计方程, 插补估计

Abstract:

In this work, we consider a semi-parametric additive hazards regression model for right-censored 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.

Key words: censoring information, missing at random, additive hazards regression model, weighting estimating equation, imputation estimating

中图分类号:

O212.1

陈菲菲, 孙志华, 叶雪. 失效信息随机缺失时可加危险率模型的统计推断[J]. 中国科学院大学学报, 2016, 33(4): 443-453.

CHEN Feifei, SUN Zhihua, YE Xue. Statistic inference of additive hazards model when censoring indicators are missing at random[J]. , 2016, 33(4): 443-453.

参考文献

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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

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