Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, Michigan, USA.
Behav Res Methods. 2024 Dec;56(8):8540-8551. doi: 10.3758/s13428-024-02490-5. Epub 2024 Aug 26.
We present the new R package instrument to perform Bayesian estimation of person explanatory multidimensional item response theory. The package implements an exploratory multidimensional item response theory model and a higher-order multidimensional item response theory model, a type of confirmatory multidimensional item response theory. Explanation of person parameters is accomplished by fixed and random effect linear regression models. Estimation is carried out using Hamiltonian Monte Carlo in Stan. In this article, we provide a detailed description of the models; we use the instrument package to demonstrate fitting explanatory item response models with fixed and random effects (i.e., mixed modeling) of person parameters in R; and, we perform a simulation study to evaluate the performance of our implementation of the models.
我们介绍了新的 R 包 instrument,用于执行贝叶斯估计个人解释多维项目反应理论。该软件包实现了探索性多维项目反应理论模型和高阶多维项目反应理论模型,即确认性多维项目反应理论的一种类型。通过固定和随机效应线性回归模型来解释个人参数。使用 Stan 中的 Hamiltonian Monte Carlo 进行估计。在本文中,我们详细描述了这些模型;我们使用 instrument 包在 R 中演示了具有个人参数固定和随机效应(即混合建模)的解释项目反应模型的拟合;并且,我们进行了一项模拟研究来评估我们对模型实现的性能。