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.

翻译：本文探讨在线性模型框架下，右删失结果变量的R估计量直接推广问题。针对Wilcoxon（即秩线性）评分函数情形，我们提出秩统计量及其对应估计方程的自然推广形式，并证明其可分别精确表示为Ritov（1990）与Tsiatis（1990）所提估计方程类的成员。进而针对一大类有界非线性秩评分函数建立类似结论。渐近性质与方差估计均可由这些表示结果直接推导获得。残差分布函数的自相容估计量、中累积分布函数（及其必要推广形式）在本理论体系中发挥着关键作用。