A Class of Transformed Mean Residual Life Models With Censored Survival Data

• 成果类型: Article
• 署名作者: Sun, Liuquan; Zhang, Zhigang
• 署名单位: Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Memorial Sloan Kettering Cancer Center
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/jasa.2009.0130
• 发表日期: 2009
• 页码: 803-815
• 关键词: semiparametric regression; tests

摘要

The mean residual life function is an attractive alternative to the survival function or the hazard function of a survival time in practice. It provides the remaining life expectancy of a subject surviving Lip to time t. In this study. We propose a class of transformed mean residual life models for fitting survival data under right censoring. To estimate the model parameters. we make use of the inverse probability of censoring weighting approach and develop a system of estimating equations. Efficiency and robustness of the estimators are also studied. Both asymptotic and finite sample properties of the proposed estimators are established and the approach is applied to two real-life datasets collected from clinical trials.