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Stochastic ordering of the latent trait by the sum score under various polytomous IRT models

机译:在多种多态IRT模型下,总和得分对潜在性状的随机排序

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摘要

The sum score is often used to order respondents on the latent trait measured by the test. Therefore, it is desirable that under the chosen model the sum score stochastically orders the latent trait. It is known that unlike dichotomous item response theory (IRT) models, most polytomous IRT models do not imply stochastic ordering. It is unknown, however, (1) whether stochastic ordering is often or rarely violated and (2) whether violations yield a serious problem for practical data analysis. These are the central issues of this paper. First, some unanswered questions that pertain to polytomous IRT models implying stochastic ordering were investigated. Second, simulation studies were conducted to evaluate stochastic ordering in practical situations. It was found that for most polytomous IRT models that do not imply stochastic ordering, the sum score can be used safely to order respondents on the latent trait.
机译:总分通常用于根据测试测得的潜在特征对受访者进行排序。因此,希望在所选择的模型下,总和得分随机排序潜在特征。众所周知,与二分项目反应理论(IRT)模型不同,大多数多项目IRT模型并不意味着随机排序。但是,未知的是,(1)随机排序是否经常被违反或很少被违反,以及(2)违反是否对实际数据分析产生严重的问题。这些是本文的中心问题。首先,研究了涉及暗示随机排序的多态IRT模型的一些未回答的问题。其次,进行了仿真研究,以评估实际情况下的随机排序。研究发现,对于大多数不暗示随机排序的IRT模型,总分可以安全地用于对潜在特征的受访者进行排序。

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