Conditional quantile residual lifetime models for right censored data

Quantile residual lifetime function is a more comprehensive quantitative measure for residual lifetimes than the mean residual lifetime function. It also incorporates the median residual life function, which is less restrictive than the model based on the mean residual lifetime. In this study, we propose a semiparametric estimator of the conditional quantile residual lifetime under different covariate effects at a specified time point by the reinforcement of the auxiliary models. Two kind of test statistics are proposed to compare two quantile residual lifetimes at fixed time points. Asymptotic properties are also established and a revised bootstrap method is proposed to estimate the asymptotic variance of the estimator. Simulation studies are reported to assess the finite sample properties of the proposed estimator and the performance of test statistics in terms of type I error probabilities and powers at fixed time points. We also compare the proposed method with the method of Jung et al. (Biometrics 65:1203–1212, 2009) through simulation studies. The proposed methods are applied to HIV data and some interesting results are presented.