Abstract Developing effective individualized treatment rules (ITRs) for diseases is an important goal of clinical research. Much effort has been devoted to estimating individualized treatment effects in the recent literature. However, there have not been systematic studies on the robust inference for individualized treatment effects when there exist potential outliers. We propose a monotone ITR in the framework of a semiparametric generalized regression with two treatments and estimate the treatment effects via a smoothed maximum rank correlation procedure. We provide sufficient conditions under which the proposed estimator has an asymptotically normal distribution whose variance can be consistently estimated based on a resampling procedure. We evaluate the finite-sample properties of our proposed approach via simulation studies. We also illustrate the proposed method by applying it to a data set from an AIDS clinical trials study.

中文翻译：

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一种基于等级的方法来估计单调个性化的两种治疗方案

摘要 制定有效的疾病个体化治疗规则（ITRs）是临床研究的重要目标。在最近的文献中，很多努力致力于估计个体化治疗效果。然而，当存在潜在异常值时，尚未对个体化治疗效果的稳健推断进行系统研究。我们在具有两种治疗的半参数广义回归框架中提出了单调 ITR，并通过平滑的最大秩相关程序估计治疗效果。我们提供了充分条件，在该条件下，建议的估计量具有渐近正态分布，其方差可以基于重采样程序进行一致估计。我们通过模拟研究评估了我们提出的方法的有限样本特性。