Estimating cross quantile residual ratio with left-truncated semi-competing risks data. Issue 4 (October 2018)

• Record Type: Journal Article
• Authors: Yang, Jing; Peng, Limin
• Is Part Of: Lifetime data analysis. Volume 24:Issue 4(2018)
• Page Start: 652
• Page End: 674
• Publication Date: 2018-10
• Subjects: Estimating equation -- Left truncation -- Quantile residual time -- Semi-competing risks
• DOI: 10.1007/s10985-017-9412-5
• Languages: English
• ISSNs: 1380-7870

Abstract

Abstract A semi-competing risks setting often arises in biomedical studies, involving both a nonterminal event and a terminal event. Cross quantile residual ratio (Yang and Peng in Biometrics 72:770–779, 2016) offers a flexible and robust perspective to study the dependency between the nonterminal and the terminal events which can shed useful scientific insight. In this paper, we propose a new nonparametric estimator of this dependence measure with left truncated semi-competing risks data. The new estimator overcomes the limitation of the existing estimator that is resulted from demanding a strong assumption on the truncation mechanism. We establish the asymptotic properties of the proposed estimator and develop inference procedures accordingly. Simulation studies suggest good finite-sample performance of the proposed method. Our proposal is illustrated via an application to Denmark diabetes registry data.