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Investigating Repeater Effects on Small Sample Equating: Include or Exclude?
Applied Measurement in Education ( IF 1.528 ) Pub Date : 2020-02-18 , DOI: 10.1080/08957347.2019.1674302
Hongyu Diao 1 , Lisa Keller 1
Affiliation  

ABSTRACT

Examinees who attempt the same test multiple times are often referred to as “repeaters.” Previous studies suggested that repeaters should be excluded from the total sample before equating because repeater groups are distinguishable from non-repeater groups. In addition, repeaters might memorize anchor items, causing item drift under a non-equivalent anchor test (NEAT) design. However, under small sample equating conditions, removing repeaters might lead to smaller sample size, which increases sampling errors. Therefore, three solutions were investigated in the current study: 1) excluding repeaters, 2) excluding drifted anchor items, and 3) applying Rasch true score equating to maintain the population invariance if repeaters were removed. The results suggested excluding repeaters if the anchor were exposed to them. Circle arc equating can be applied if it is impossible to exclude all drifted anchor items. Applying Rasch true did outperform solutions.



中文翻译:

研究中继器对小样本均等化的影响:包括还是排除?

摘要

多次尝试相同测试的考生通常称为“重复考生”。先前的研究表明,在等同之前,应将中继器从总样本中排除,因为中继器组与非中继器组是有区别的。此外,中继器可能会记住锚项目,从而在非等效锚测试(NEAT)设计下导致项目漂移。但是,在小样本等值条件下,删除中继器可能会导致样本大小变小,从而增加采样误差。因此,在本研究中,研究了三种解决方案:1)不包括中继器,2)不包括漂移的锚项目,以及3)应用Rasch true分数等于如果除去中继器则保持种群不变性。结果表明,如果锚钉暴露在中继器上,则不包括中继器。如果不可能排除所有漂移的锚项目,则可以应用圆弧等距。应用Rasch true确实胜过解决方案。

更新日期:2020-02-18
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