Department of Psychology, University of Southern California, Los Angeles, CA, USA.
School of Human Services, University of Cincinnati, Cincinnati, OH, USA.
Addict Behav. 2019 Jul;94:50-56. doi: 10.1016/j.addbeh.2018.11.029. Epub 2018 Nov 22.
Establishing measurement invariance, or that an instrument measures the same construct(s) in the same way across subgroups of respondents, is crucial in efforts to validate social and behavioral instruments. Although substantial previous research has focused on detecting the presence of noninvariance, less attention has been devoted to its practical significance and even less has been paid to its possible impact on diagnostic accuracy. In this article, we draw additional attention to the importance of measurement invariance and advance diagnostic research by introducing a novel approach for quantifying the impact of noninvariance with binary items (e.g., the presence or absence of symptoms). We illustrate this approach by testing measurement invariance and evaluating diagnostic accuracy across age groups using DSM alcohol use disorder items from a public national data set. By providing researchers with an easy-to-implement R program for examining diagnostic accuracy with binary items, this article sets the stage for future evaluations of the practical significance of partial invariance. Future work can extend our framework to include ordinal and categorical indicators, other measurement models in item response theory, settings with three or more groups, and via comparison to an external, "gold-standard" validator.
在努力验证社会和行为科学工具时，建立测量不变性（即工具在受访者的子组中以相同的方式测量相同的结构）至关重要。尽管先前有大量研究集中于检测非不变性的存在，但对其实际意义的关注较少，甚至对其对诊断准确性的可能影响的关注更少。在本文中，我们通过引入一种量化具有二项式项目（例如，症状的存在或不存在）的非不变性的影响的新方法，进一步强调了测量不变性的重要性，并推进了诊断研究。我们通过使用来自公共国家数据集的 DSM 酒精使用障碍项目测试年龄组之间的测量不变性和评估诊断准确性来说明这种方法。通过为研究人员提供一个易于实现的 R 程序来检查具有二项式项目的诊断准确性，本文为未来评估部分不变性的实际意义奠定了基础。未来的工作可以扩展我们的框架，包括有序和分类指标、项目反应理论中的其他测量模型、具有三个或更多组的设置，以及通过与外部“黄金标准”验证器进行比较。
