Department of Psychology, Central Michigan University.
Psychol Assess. 2019 Dec;31(12):1481-1496. doi: 10.1037/pas0000731.
One of the most important considerations in psychological and educational assessment is the extent to which a test is free of bias and fair for groups with diverse backgrounds. Establishing measurement invariance (MI) of a test or items is a prerequisite for meaningful comparisons across groups as it ensures that test items do not function differently across groups. Demonstration of MI is particularly important in assessment settings where test scores are used in decision making. In this review, we begin with an overview of test bias and fairness, followed by a discussion of issues involving group classification, focusing on categorizations of race/ethnicity and sex/gender. We then describe procedures used to establish MI, detailing steps in the implementation of multigroup confirmatory factor analysis, and discussing recent developments in alternative procedures for establishing MI, such as the alignment method and moderated nonlinear factor analysis, which accommodate reconceptualization of group categorizations. Lastly, we discuss a variety of important statistical and conceptual issues to be considered in conducting multigroup confirmatory factor analysis and related methods and conclude with some recommendations for applications of these procedures. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
在心理和教育评估中,最重要的考虑因素之一是测试在多大程度上不受偏见影响,并且对具有不同背景的群体公平。建立测试或项目的测量不变性(MI)是跨群体进行有意义比较的前提,因为它确保测试项目在不同群体中不会有不同的功能。在评估环境中,当测试分数用于决策时,MI 的证明尤为重要。在这篇综述中,我们首先概述了测试的偏差和公平性,然后讨论了涉及群体分类的问题,重点是种族/民族和性别/性别分类。然后,我们描述了建立 MI 的程序,详细介绍了多组验证性因素分析实施的步骤,并讨论了建立 MI 的替代程序的最新发展,例如对齐方法和适度非线性因素分析,这些方法适应了群体分类的重新概念化。最后,我们讨论了在进行多组验证性因素分析和相关方法时需要考虑的各种重要的统计和概念问题,并对这些程序的应用提出了一些建议。(PsycINFO 数据库记录(c)2019 APA,保留所有权利)。