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Kernel Equating Under the Non-Equivalent Groups With Covariates Design

机译:具有协变量设计的非对等组下的核等式

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摘要

When equating two tests, the traditional approach is to use common test takers and/or common items. Here, the idea is to use variables correlated with the test scores (e.g., school grades and other test scores) as a substitute for common items in a non-equivalent groups with covariates (NEC) design. This is performed in the framework of kernel equating and with an extension of the method developed for post-stratification equating in the non-equivalent groups with anchor test design. Real data from a college admissions test were used to illustrate the use of the design. The equated scores from the NEC design were compared with equated scores from the equivalent group (EG) design, that is, equating with no covariates as well as with equated scores when a constructed anchor test was used. The results indicate that the NEC design can produce lower standard errors compared with an EG design. When covariates were used together with an anchor test, the smallest standard errors were obtained over a large range of test scores. The results obtained, that an EG design equating can be improved by adjusting for differences in test score distributions caused by differences in the distribution of covariates, are useful in practice because not all standardized tests have anchor tests.
机译:当等同于两个测试时,传统的方法是使用共同的应试者和/或共同的项目。这里的想法是使用与考试成绩相关的变量(例如学校成绩和其他考试成绩)代替具有协变量(NEC)设计的非对等组中的常见项目。这是在核对等的框架内进行的,并扩展了为使用锚定测试设计在非对等组中进行后分层等化而开发的方法的扩展。来自大学入学考试的真实数据用于说明设计的用途。将来自NEC设计的等值分数与来自等效组(EG)设计的等值分数进行比较,也就是说,在使用构建的锚定测试时,既没有协变量也等于等分。结果表明,与EG设计相比,NEC设计可以产生更低的标准误差。当协变量与锚定检验一起使用时,在较大的测试分数范围内可获得最小的标准误差。所获得的结果表明,可以通过调整因协变量分布的差异而导致的测验分数分布的差异来改善EG设计的等效性,这在实践中很有用,因为并非所有标准化测试都具有锚定测试。

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