Work

R-estimation with right-censored data

Year: 2026

Type: article

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.

Source: Lifetime Data Analysis

DOI: 10.1007/s10985-026-09733-x

Authors: Glen A. Satten, Mo Li, Ni Zhao, Robert L. Strawderman

Institutions: Emory University, University of Louisiana at Lafayette, Johns Hopkins University, University of Rochester Medicine, University of Rochester

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,090

Funders: National Institutes of Health, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences