一个多层混合IRT框架建模反应时间作为IRT模型中反应参与的预测或指标。

IF 2.1 3区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Educational and Psychological Measurement Pub Date : 2022-10-01 Epub Date: 2021-09-13 DOI:10.1177/00131644211045351
Gabriel Nagy, Esther Ulitzsch
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引用次数: 19

摘要

不参与的项目反应对大规模评估提供的结果的有效性构成威胁。根据观察到的反应时间,已经提出了几种识别不参与反应的程序,并提出了反应参与的项目反应理论(IRT)模型。我们概述了基于反应时间的反应参与分类程序和反应参与的IRT模型是基于共同的思想,我们提出了独立和依赖潜在类IRT模型之间的区别。在考虑的所有IRT模型中,反应参与度由项目级潜在类别变量表示,但模型假设反应时间反映或预测参与度。我们总结了属于每个组的现有IRT模型,并对其进行扩展以增加其灵活性。此外,我们提出了一个灵活的多层混合IRT框架,其中所有IRT模型都可以通过边际极大似然来估计。该框架基于广泛使用的Mplus软件,从而使该过程能够为广泛的受众所访问。这些程序是根据公开的大规模数据来说明的。我们的研究结果表明,不同的反应参与IRT模型对个体熟练程度估计的项目参数的调整与传统的IRT模型略有不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Multilevel Mixture IRT Framework for Modeling Response Times as Predictors or Indicators of Response Engagement in IRT Models.

A Multilevel Mixture IRT Framework for Modeling Response Times as Predictors or Indicators of Response Engagement in IRT Models.

A Multilevel Mixture IRT Framework for Modeling Response Times as Predictors or Indicators of Response Engagement in IRT Models.

A Multilevel Mixture IRT Framework for Modeling Response Times as Predictors or Indicators of Response Engagement in IRT Models.

Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based procedures for classifying response engagement and IRT models for response engagement are based on common ideas, and we propose the distinction between independent and dependent latent class IRT models. In all IRT models considered, response engagement is represented by an item-level latent class variable, but the models assume that response times either reflect or predict engagement. We summarize existing IRT models that belong to each group and extend them to increase their flexibility. Furthermore, we propose a flexible multilevel mixture IRT framework in which all IRT models can be estimated by means of marginal maximum likelihood. The framework is based on the widespread Mplus software, thereby making the procedure accessible to a broad audience. The procedures are illustrated on the basis of publicly available large-scale data. Our results show that the different IRT models for response engagement provided slightly different adjustments of item parameters of individuals' proficiency estimates relative to a conventional IRT model.

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来源期刊
Educational and Psychological Measurement
Educational and Psychological Measurement 医学-数学跨学科应用
CiteScore
5.50
自引率
7.40%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Educational and Psychological Measurement (EPM) publishes referred scholarly work from all academic disciplines interested in the study of measurement theory, problems, and issues. Theoretical articles address new developments and techniques, and applied articles deal with innovation applications.
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