R-estimation with right-censored data.
4 affiliations
- 1Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA.
- 2Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA, USA.
- 3Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
- 4Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA. [email protected].
Abstract
This paper considers the problem of directly generalizing the R-estimator under a linear model formulation with right-censored outcomes. We propose a natural generalization of the rank and corresponding estimating equation for the R-estimator in the case of the Wilcoxon (i.e., linear-in-ranks) score function, and show how it can respectively be exactly represented as members of the classes of estimating equations proposed in Ritov (1990) and Tsiatis (1990). We then establish analogous results for a large class of bounded nonlinear-in-ranks score functions. Asymptotics and variance estimation are obtained as straightforward consequences of these representation results. The self-consistent estimator of the residual distribution function, and the mid-cumulative distribution function (and, where needed, a generalization of it), play critical roles in these developments.
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BibTeX
@article{satten2026restimation,
title = {{R-estimation with right-censored data.}},
author = {Glen A Satten and Mo Li and Ni Zhao and Robert L Strawderman},
journal = {Lifetime data analysis},
year = {2026},
month = oct,
doi = {10.1007/s10985-026-09733-x},
url = {https://europepmc.org/article/MED/42900297},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - R-estimation with right-censored data.
AU - Glen A Satten
AU - Mo Li
AU - Ni Zhao
AU - Robert L Strawderman
PY - 2026
DA - 2026/10/20
JO - Lifetime data analysis
DO - 10.1007/s10985-026-09733-x
UR - https://europepmc.org/article/MED/42900297
AB - This paper considers the problem of directly generalizing the R-estimator under a linear model formulation with right-censored outcomes. We propose a natural generalization of the rank and corresponding estimating equation for the R-estimator in the case of the Wilcoxon (i.e., linear-in-ranks) score function, and show how it can respectively be exactly represented as members of the classes of estimating equations proposed in Ritov (1990) and Tsiatis (1990). We then establish analogous results for a large class of bounded nonlinear-in-ranks score functions. Asymptotics and variance estimation are obtained as straightforward consequences of these representation results. The self-consistent estimator of the residual distribution function, and the mid-cumulative distribution function (and, where needed, a generalization of it), play critical roles in these developments.
SN - 1380-7870
SN - 1572-9249
ER -