A Mixed Sequential IRT Model for Mixed-Format Items.

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Applied Psychological Measurement Pub Date : 2023-06-01 Epub Date: 2023-03-17 DOI:10.1177/01466216231165302
Junhuan Wei, Yan Cai, Dongbo Tu
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引用次数: 0

Abstract

To provide more insight into an individual's response process and cognitive process, this study proposed three mixed sequential item response models (MS-IRMs) for mixed-format items consisting of a mixture of a multiple-choice item and an open-ended item that emphasize a sequential response process and are scored sequentially. Relative to existing polytomous models such as the graded response model (GRM), generalized partial credit model (GPCM), or traditional sequential Rasch model (SRM), the proposed models employ an appropriate processing function for each task to improve conventional polytomous models. Simulation studies were carried out to investigate the performance of the proposed models, and the results indicated that all proposed models outperformed the SRM, GRM, and GPCM in terms of parameter recovery and model fit. An application illustration of the MS-IRMs in comparison with traditional models was demonstrated by using real data from TIMSS 2007.

混合格式项目的混合序列 IRT 模型。
为了更深入地了解个体的反应过程和认知过程,本研究提出了三种混合序列项目反应模型(MS-IRM),适用于由选择题和开放题混合组成的混合格式项目,这些项目强调序列反应过程并按序列计分。相对于现有的多项式模型,如分级反应模型(GRM)、广义部分学分模型(GPCM)或传统的序列拉希模型(SRM),所提出的模型为每个任务采用了适当的处理函数,以改进传统的多项式模型。研究人员进行了仿真研究以考察所提模型的性能,结果表明,所有所提模型在参数恢复和模型拟合方面均优于 SRM、GRM 和 GPCM。通过使用 TIMSS 2007 的真实数据,展示了 MS-IRM 与传统模型的应用比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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