Institute for Learning Sciences & Teacher Education, Australian Catholic University, Brisbane, Queensland, Australia.
Faculty of Education, The University of Hong Kong, Hong Kong, China.
Br J Math Stat Psychol. 2023 Nov;76(3):491-512. doi: 10.1111/bmsp.12303. Epub 2023 Mar 26.
The use of multidimensional forced-choice (MFC) items to assess non-cognitive traits such as personality, interests and values in psychological tests has a long history, because MFC items show strengths in preventing response bias. Recently, there has been a surge of interest in developing item response theory (IRT) models for MFC items. However, nearly all of the existing IRT models have been developed for MFC items with binary scores. Real tests use MFC items with more than two categories; such items are more informative than their binary counterparts. This study developed a new IRT model for polytomous MFC items based on the cognitive model of choice, which describes the cognitive processes underlying humans' preferential choice behaviours. The new model is unique in its ability to account for the ipsative nature of polytomous MFC items, to assess individual psychological differentiation in interests, values and emotions, and to compare the differentiation levels of latent traits between individuals. Simulation studies were conducted to examine the parameter recovery of the new model with existing computer programs. The results showed that both statement parameters and person parameters were well recovered when the sample size was sufficient. The more complete the linking of the statements was, the more accurate the parameter estimation was. This paper provides an empirical example of a career interest test using four-category MFC items. Although some aspects of the model (e.g., the nature of the person parameters) require additional validation, our approach appears promising.
多维强迫选择(MFC)项目在心理测试中用于评估非认知特质,如人格、兴趣和价值观,其历史悠久,因为 MFC 项目在防止反应偏差方面具有优势。最近,人们对开发多维强迫选择项目的项目反应理论(IRT)模型产生了浓厚的兴趣。然而,几乎所有现有的 IRT 模型都是针对二进制得分的 MFC 项目开发的。实际测试使用的 MFC 项目有两个以上的类别;这些项目比二进制对应物更具信息量。本研究基于选择的认知模型,为多项 MFC 项目开发了一种新的 IRT 模型,该模型描述了人类偏好选择行为背后的认知过程。新模型的独特之处在于能够解释多项 MFC 项目的特质性,评估兴趣、价值观和情感方面的个体心理差异,并比较个体之间潜在特质的分化水平。通过使用现有的计算机程序进行模拟研究,考察了新模型的参数恢复情况。结果表明,当样本量足够大时,语句参数和个体参数都能得到很好的恢复。语句的链接越完整,参数估计就越准确。本文提供了一个使用四项 MFC 项目的职业兴趣测试的实证示例。尽管模型的某些方面(例如,个体参数的性质)需要进一步验证,但我们的方法似乎很有前景。