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Computer Adaptive Test Stopping Rules Applied to The Flexilevel Shoulder Functioning Test

机译:计算机自适应测试停止规则应用于FlexileVel肩部功能测试

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摘要

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.
机译:电脑式自适应测试(CAT)是传统纸张和铅笔测试的有吸引力的替代方案,因为它可以提供比线性测试形式更少的物品在较少的情况下提供准确的特质估计。停止规则是确定评估效率的重要因素。该仿真比较了.3,最小信息(MI)的三个可变长度停止规则标准误差(MI)和.02的特征(CT)的变化,没有最大数量的项目(20) 。我们使用10和20项的固定长度标准作为两种版本的线性评估的比较。与其他规则相比,MI规则导致更长的评估具有更多偏见的特质估计数。 CT规则在特征尺度的较高端和更大的标准误差下产生更多偏置估计。在测量精度和效率方面,SE规则在特征范围内进行了良好。

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