柔性肩功能测试中计算机自适应测试停止规则的应用

Journal of applied measurement Pub Date : 2019-01-01
Trenton J Combs, Kyle W English, Barbara G Dodd, Hyeon-Ah Kang
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引用次数: 0

摘要

计算机自适应测试(CAT)是传统纸笔测试的一个有吸引力的替代方案,因为它可以提供准确的特征估计,同时管理比线性测试形式更少的项目。停止规则是决定评估效率的重要因素。这个模拟比较了三个可变长度停止规则——标准误差(SE)为0.3,最小信息(MI)为0.7,特征变化(CT)为0.02——有和没有施加最大数量的项目(20)。我们使用10和20个项目的固定长度标准作为线性评估的两个版本的比较。与其他规则相比,MI规则导致更长的评估时间和更有偏见的特征估计。CT规则导致在性状量表的较高端产生更多的偏倚估计和更大的标准误差。在测量精度和效率方面,SE规则在性状量表上表现良好。
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Computer Adaptive Test Stopping Rules Applied to The Flexilevel Shoulder Functioning Test.

Computerized adaptive testing (CAT) is an attractive alternative to traditional paper-and-pencil testing because it can provide accurate trait estimates while administering fewer items than a linear test form. A stopping rule is an important factor in determining an assessments efficiency. This simulation compares three variable-length stopping rules-standard error (SE) of .3, minimum information (MI) of .7 and change in trait (CT) of .02 - with and without a maximum number of items (20) imposed. We use fixed-length criteria of 10 and 20 items as a comparison for two versions of a linear assessment. The MI rules resulted in longer assessments with more biased trait estimates in comparison to other rules. The CT rule resulted in more biased estimates at the higher end of the trait scale and larger standard errors. The SE rules performed well across the trait scale in terms of both measurement precision and efficiency.

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