Censored quantile regression with time-dependent covariates

• 成果类型: Article; Early Access
• 署名作者: Chu, Chi Wing; Sit, Tony; Ying, Zhiliang
• 署名单位: City University of Hong Kong; Chinese University of Hong Kong; Columbia University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1093/jrsssb/qkaf042
• 发表日期: 2025
• 关键词: survival analysis; MODEL; indinavir

摘要

We propose a new class of censored quantile regression models with time-dependent covariates for right-censored failure time data. While time-dependent covariates naturally arise in time-to-event analysis, existing works in the literature discuss treatments for data collected either under an independent censoring mechanism or a longitudinal setting. Our formulation extends the current scope so that the conventional setting of time-dependent covariates can be properly handled. The new framework also generalizes the definition of quantiles and offers a new dynamic perspective for interpretation. Asymptotic properties of the recursive estimator are established. Numerical studies are also presented to illustrate the effectiveness of our proposal.