Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.
Department of Informatics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
Behav Res Methods. 2023 Sep;55(6):3129-3148. doi: 10.3758/s13428-022-01947-9. Epub 2022 Sep 7.
Rasch analysis is a procedure to develop and validate instruments that aim to measure a person's traits. However, manual Rasch analysis is a complex and time-consuming task, even more so when the possibility of differential item functioning (DIF) is taken into consideration. Furthermore, manual Rasch analysis by construction relies on a modeler's subjective choices. As an alternative approach, we introduce a semi-automated procedure that is based on the optimization of a new criterion, called in-plus-out-of-questionnaire log likelihood with differential item functioning (IPOQ-LL-DIF), which extends our previous criterion. We illustrate our procedure on artificially generated data as well as on several real-world datasets containing potential DIF items. On these real-world datasets, our procedure found instruments with similar clinimetric properties as those suggested by experts through manual analyses.
Rasch 分析是一种开发和验证旨在衡量个体特质的工具的方法。然而，手动 Rasch 分析是一项复杂且耗时的任务，特别是当考虑到项目功能差异（DIF）的可能性时更是如此。此外，手动 Rasch 分析的构建依赖于建模者的主观选择。作为一种替代方法，我们引入了一种半自动化的程序，该程序基于优化一个新的标准，称为具有项目功能差异的问卷内加外失拟对数似然比（IPOQ-LL-DIF），这是我们之前标准的扩展。我们在人为生成的数据以及包含潜在 DIF 项目的几个真实世界数据集上说明了我们的程序。在这些真实世界的数据集中，我们的程序找到了具有与专家通过手动分析建议的类似临床特性的工具。
