Department of Psychology, University of Zurich, Switzerland.
Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Switzerland.
Br J Math Stat Psychol. 2022 Nov;75(3):728-752. doi: 10.1111/bmsp.12275. Epub 2022 Jun 6.
A family of score-based tests has been proposed in recent years for assessing the invariance of model parameters in several models of item response theory (IRT). These tests were originally developed in a maximum likelihood framework. This study discusses analogous tests for Bayesian maximum-a-posteriori estimates and multiple-group IRT models. We propose two families of statistical tests, which are based on an approximation using a pooled variance method, or on a simulation approach based on asymptotic results. The resulting tests were evaluated by a simulation study, which investigated their sensitivity against differential item functioning with respect to a categorical or continuous person covariate in the two- and three-parametric logistic models. Whereas the method based on pooled variance was found to be useful in practice with maximum likelihood as well as maximum-a-posteriori estimates, the simulation-based approach was found to require large sample sizes to lead to satisfactory results.
近年来，提出了一类基于得分的检验方法，用于评估项目反应理论（IRT）中几种模型的模型参数不变性。这些检验最初是在最大似然框架中开发的。本研究讨论了贝叶斯最大后验估计和多组 IRT 模型的类似检验。我们提出了两类统计检验，它们基于使用合并方差方法的近似值，或基于渐近结果的模拟方法。通过模拟研究评估了得到的检验，该研究调查了它们对二参数和三参数逻辑模型中类别或连续个体协变量的差异项目功能的敏感性。尽管基于合并方差的方法在最大似然和最大后验估计中都被发现具有实际用途，但基于模拟的方法发现需要大样本量才能得到令人满意的结果。
