Censored quantile regression with time-dependent covariates
Abstract 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.
Authors
- Tony Sit (ORCID: https://orcid.org/0000-0001-5006-1838)
- Chi Wing Chu (ORCID: https://orcid.org/0000-0002-1527-8414)
- Zhiliang Ying
Institutions
- City University of Hong Kong (HK)
- Chinese University of Hong Kong (HK)
- Columbia University (US)
Publication Details
- Journal
- Journal of the Royal Statistical Society Series B (Statistical Methodology)
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1093/jrsssb/qkaf042
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Research Grants Council, University Grants Committee