The quantile residual lifetime (QRL) regression is an attractive tool for assessing covariate effects on the distribution of residual life expectancy, which is often of interest in clinical studies. When the study subjects are exposed to multiple events of interest, the failure times observed for the same subject are potentially correlated. To address such correlation in assessing the covariate effects on QRL, we propose a marginal semiparametric QRL regression model for multivariate failure time data. Our new proposal facilitates estimation of the model parameters using unbiased estimating equations and results in estimators, which are shown to be consistent and asymptotically normal. To overcome additional challenges in inference, we provide three methods for variance estimation based on resampling techniques and a sandwich estimator, and further develop a Wald-type test statistic for inference. The simulation studies and a real data analysis offer evidence of the satisfactory performance of the proposed method.

翻译：分位数剩余寿命回归是评估协变量对剩余寿命期望分布影响的有力工具，在临床研究中具有重要意义。当研究对象经历多个相关事件时，同一受试者观察到的失效时间可能存在相关性。为在评估协变量对分位数剩余寿命影响时处理此类相关性，本文针对多元失效时间数据提出了一种边际半参数分位数剩余寿命回归模型。该新方法通过无偏估计方程实现模型参数估计，所得估计量具有一致性和渐近正态性。为克服推断中的额外挑战，我们基于重采样技术和三明治估计量提出了三种方差估计方法，并进一步构建了Wald型检验统计量进行统计推断。模拟研究和实际数据分析均表明所提方法具有令人满意的性能。