Lou Yichen, Du Mingyue, Wang Peijie, Song Xinyuan
Department of Statistics, The Chinese University of Hong Kong, Hong Kong.
School of Mathematics, Jilin University, China.
Stat Methods Med Res. 2025 Jul 14:9622802251356592. doi: 10.1177/09622802251356592.
This article discusses regression analysis of interval-censored failure time data in the presence of a cure fraction and nonignorable missing covariates. To address the challenges caused by interval censoring, missing covariates and the existence of a cure subgroup, we propose a joint semiparametric modeling framework that simultaneously models the failure time of interest and the missing covariates. In particular, we present a class of semiparametric nonmixture cure models for the failure time and a semiparametric density ratio model for the missing covariates. A two-step likelihood-based estimation procedure is developed and the large sample properties of the resulting estimators are established. An extensive numerical study demonstrates the good performance of the proposed method in practical settings and the proposed approach is applied to an Alzheimer's disease study that motivated this study.
本文讨论了在存在治愈比例和不可忽略的缺失协变量情况下，区间删失失效时间数据的回归分析。为应对区间删失、缺失协变量以及治愈亚组的存在所带来的挑战，我们提出了一个联合半参数建模框架，该框架同时对感兴趣的失效时间和缺失协变量进行建模。具体而言，我们给出了一类针对失效时间的半参数非混合治愈模型以及针对缺失协变量的半参数密度比模型。开发了一种基于似然的两步估计程序，并建立了所得估计量的大样本性质。广泛的数值研究证明了所提方法在实际场景中的良好性能，并且所提方法被应用于一项激发本研究的阿尔茨海默病研究。
