混合IRT潜在模型及其应用轨迹

The Mixture Item Response Theory Models and Its Application Traces

项目反应理论是测量被试潜在特质的现代测量理论,潜在类别分析是基于模型的潜在特质分类技术。混合项目反应理论将项目反应理论与潜在类别分析相结合,能够同时对被试分类并量化其潜在特质。在阐述混合项目反应理论概念、原理的基础上,介绍了MRM、mNRM和mPCM等几种常见混合模型及其参数估计方法,并从心理与行为特征分类、项目功能差异检测、测验效度评价等方面评述了其在心理测验中的应用发展轨迹。

Item response theory （IRT） is a modern measurement theory for accurately estimating individuals＇ ability, and latent class analysis （LCA） is a statistical technique used to identify subtypes of individuals, which is based on statistic models. Mixture item response theory （Mixture IRT）[0] combining LCA and IRT is able to classify the subjects as well as quantifying their traits. The concept and principle of Mixture IRT is elaborated in this paper. Besides, several common mixed models are introduced here, such as the mixed Rasch model （MRM）, a mixture version of the nominal response model （mNRM） and a mixture version of the partial credit model （mPCM）. Furthermore, different parameter estimation methods are described and the application traces in psychological test of Mixture IRT is evaluated from the perspectives of classifying psychological or behavioral traits, detecting differential item functioning and estimating test validity.