Confirming Testlet Effects
Confirming Testlet Effects
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DOI：
10.1177/0146621612437403
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发表时间：
2012-03-01
影响因子：
1.2
通讯作者：
DeMars, Christine E.
中科院分区：
文献类型：
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作者：
DeMars, Christine E.
小测试是一组项目，它们共享一个共同的段落、场景或其他上下文。这些项目可能测量的共同点超出了测试作为一个整体测量的特质;如果是这样，项目反应的模型应该允许这个小测试特质。但是，对可忽略的测试样本效应进行建模会使模型变得不必要的复杂，并冒着偶然资本化的风险，增加了参数估计的误差。因此，检查每个testlet以查看testlet中的项目是否共享主要特征之外的某些内容可能是有用的。该研究包括（a）无testlet的模型与有testlet g的模型之间的比较，（B）有所有可疑testlet的模型与有除testlet g外的所有可疑testlet的模型之间的比较，以及（c）基本一维性的测试。总体而言，比较B是最有用的检测小测验的影响。基于信息标准的模型比较，特别是样本量调整贝叶斯信息标准（SSA-BIC）和BIC，导致比统计显著性检验更少的误报。当测试集效应为零时，除了研究的测试集之外，基本一维性的测试具有与SSA-BIC相似的真实命中率和误报率。但是，在划分测试中存在额外的小测验效应导致了更高的误报率的测试基本的一维性。
A testlet is a cluster of items that share a common passage, scenario, or other context. These items might measure something in common beyond the trait measured by the test as a whole; if so, the model for the item responses should allow for this testlet trait. But modeling testlet effects that are negligible makes the model unnecessarily complicated and risks capitalization on chance, increasing the error in parameter estimates. Checking each testlet to see if the items within the testlet share something beyond the primary trait could therefore be useful. This study included (a) comparison between a model with no testlets and a model with testlet g, (b) comparison between a model with all suspected testlets and a model with all suspected testlets except testlet g, and (c) a test of essential unidimensionality. Overall, Comparison b was most useful for detecting testlet effects. Model comparisons based on information criteria, specifically the sample-size adjusted Bayesian Information Criteria (SSA-BIC) and BIC, resulted in fewer false alarms than statistical significance tests. The test of essential unidimensionality had true hit rates and false alarm rates similar to the SSA-BIC when the testlet effect was zero for all testlets except the studied testlet. But the presence of additional testlet effects in the partitioning test led to higher false alarm rates for the test of essential unidimensionality.