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. © The Royal Statistical Society 2025.
| Original language | English |
|---|---|
| Article number | qkaf042 |
| Pages (from-to) | 66-90 |
| Journal | Journal of the Royal Statistical Society. Series B: Statistical Methodology |
| Volume | 88 |
| Issue number | 1 |
| Online published | 6 Aug 2025 |
| DOIs | |
| Publication status | Published - Feb 2026 |
Funding
C.W.C. work was partially supported by Hong Kong Research Grants Council RGC-21505524. T.S. work was partially supported by Hong Kong Research Grants Council RGC-14301920, and RGC-14307221.
Research Keywords
- censored data
- empirical process
- quantile regression
- survival analysis
- time-dependent covariates
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC 4.0. https://creativecommons.org/licenses/by-nc/4.0/
RGC Funding Information
- RGC-funded
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