Screening measures are used in psychology and medicine to identify respondents who are high or low on a construct. Based on the screening, the evaluator assigns respondents to classes corresponding to different courses of action: Make a diagnosis versus reject a diagnosis; provide services versus withhold services; or conduct further assessment versus conclude the assessment process. When measures are used to classify individuals, it is important that the decisions be consistent and equitable across groups. Ideally, if respondents completed the screening measure repeatedly in quick succession, they would be consistently assigned into the same class each time. In addition, the consistency of the classification should be unrelated to the respondents' background characteristics, such as sex, race, or ethnicity (i.e., the measure is free of measurement bias). Reporting estimates of classification consistency is a common practice in educational testing, but there has been limited application of these estimates to screening in psychology and medicine. In this article, we present two procedures based on item response theory that are used (a) to estimate the classification consistency of a screening measure and (b) to evaluate how classification consistency is impacted by measurement bias across respondent groups. We provide R functions to conduct the procedures, illustrate the procedures with real data, and use Monte Carlo simulations to guide their appropriate use. Finally, we discuss how estimates of classification consistency can help assessment specialists make more informed decisions on the use of a screening measure with protected groups (e.g., groups defined by gender, race, or ethnicity). (PsycInfo Database Record (c) 2021 APA, all rights reserved).

中文翻译：

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估计筛选措施的分类一致性并量化测量偏差的影响。

筛选措施用于心理学和医学，以识别在结构上高或低的受访者。根据筛选，评估者将受访者分配到与不同行动方案相对应的类别：做出诊断与拒绝诊断；提供服务与扣留服务；或进行进一步评估而不是结束评估过程。当使用措施对个人进行分类时，重要的是决策在群体之间保持一致和公平。理想情况下，如果受访者连续快速地重复完成筛选措施，他们每次都会被一致地分配到同一个班级。此外，分类的一致性应与受访者的背景特征无关，例如性别、种族或民族（即，该措施没有测量偏差）。报告分类一致性的估计是教育测试中的一种常见做法，但这些估计在心理学和医学筛查中的应用有限。在本文中，我们提出了两个基于项目响应理论的程序，它们用于 (a) 估计筛选测量的分类一致性和 (b) 评估分类一致性如何受到受访者群体测量偏差的影响。我们提供 R 函数来执行程序，用真实数据说明程序，并使用蒙特卡罗模拟来指导它们的适当使用。最后，我们讨论了分类一致性的估计如何帮助评估专家在对受保护群体使用筛查措施时做出更明智的决定（例如，按性别、种族或民族定义的群体）。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）。