The concept of broad sense agreement (BSA) has recently been proposed for studying the relationship between a continuous measurement and an ordinal measurement. They developed a nonparametric procedure for estimating the BSA index, which is only applicable to completely observed data. In this work, we consider the problem of evaluating BSA index when the continuous measurement is subject to censoring. We propose a nonparametric estimation method built upon a derivation of a new functional representation of the BSA index, which allows for accommodating censoring by plugging in the nonparametric survival function estimators. We establish the consistency and asymptotic normality for the proposed BSA estimator. We also investigate an alternative approach based on the strategy of multiple imputation, which is shown to have better empirical performance with small sample sizes than the plug‐in method. Extensive simulation studies are conducted to evaluate our proposals. We illustrate our methods via an application to a Surgical Intensive Care Unit study.

中文翻译：

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有序和审查连续结果之间广义一致性的非参数估计。

最近提出了广义一致性（BSA）的概念来研究连续测量和有序测量之间的关系。他们开发了一种用于估计 BSA 指数的非参数程序，该程序仅适用于完全观察到的数据。在这项工作中，我们考虑了当连续测量受到审查时评估 BSA 指数的问题。我们提出了一种基于 BSA 指数新函数表示的推导的非参数估计方法，该方法允许通过插入非参数生存函数估计器来适应审查。我们为所提出的 BSA 估计量建立了一致性和渐近正态性。我们还研究了一种基于多重插补策略的替代方法，事实证明，在小样本情况下，该方法比插件方法具有更好的经验性能。我们进行了广泛的模拟研究来评估我们的建议。我们通过外科重症监护室研究的应用来说明我们的方法。