基于分数的评估决策有多准确和一致？使用线性因子模型的程序。
How Accurate and Consistent Are Score-Based Assessment Decisions? A Procedure Using the Linear Factor Model.
机构信息
The University of North Carolina at Chapel Hill, USA.
Arizona State University, Tempe, USA.
出版信息
Assessment. 2023 Jul;30(5):1640-1650. doi: 10.1177/10731911221113568. Epub 2022 Aug 11.
When scales or tests are used to make decisions about individuals (e.g., to identify which adults should be assessed for psychiatric disorders), it is crucial that these decisions be accurate and consistent. However, it is not obvious how to assess accuracy and consistency when the scale was administered only once to a given sample and the true condition based on the latent variable is unknown. This article describes a method based on the linear factor model for evaluating the accuracy and consistency of scale-based decisions using data from a single administration of the scale. We illustrate the procedure and provide R code that investigators can use to apply the method in their own data. Finally, in a simulation study, we evaluate how the method performs when applied to discrete (vs. continuous) items, a practice that is common in published literature. The results suggest that the method is generally robust when applied to discrete items.
当使用量表或测试来对个体做出决策（例如，确定哪些成年人应接受精神障碍评估）时，这些决策的准确性和一致性至关重要。然而，当量表仅对给定样本进行一次施测，并且基于潜在变量的真实情况未知时，如何评估准确性和一致性并不明显。本文描述了一种基于线性因子模型的方法，用于使用量表单次施测的数据来评估基于量表的决策的准确性和一致性。我们展示了该程序，并提供了 R 代码，研究人员可以在自己的数据中应用该方法。最后，在一项模拟研究中，我们评估了当应用于离散（与连续）项目时，该方法的性能如何，这在已发表的文献中是很常见的做法。结果表明，该方法在应用于离散项目时通常是稳健的。
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