Feng Yanqin, Chen Yurong
School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, People's Republic of China.
Lifetime Data Anal. 2018 Apr;24(2):293-309. doi: 10.1007/s10985-016-9389-5. Epub 2017 Jan 5.
This paper discusses regression analysis of current status failure time data with information observations and continuous auxiliary covariates. Under the additive hazards model, we employ a frailty model to describe the relationship between the failure time of interest and censoring time through some latent variables and propose an estimated partial likelihood estimator of regression parameters that makes use of the available auxiliary information. Asymptotic properties of the resulting estimators are established. To assess the finite sample performance of the proposed method, an extensive simulation study is conducted, and the results indicate that the proposed method works well. An illustrative example is also provided.
本文讨论了具有信息观测值和连续辅助协变量的当前状态失效时间数据的回归分析。在加性风险模型下，我们采用脆弱模型通过一些潜在变量来描述感兴趣的失效时间与删失时间之间的关系，并提出了一种利用可用辅助信息的回归参数估计偏似然估计量。建立了所得估计量的渐近性质。为了评估所提方法的有限样本性能，进行了广泛的模拟研究，结果表明所提方法效果良好。还提供了一个说明性示例。
