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Equating Test Scores: Toward Best Practices

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Statistical Models for Test Equating, Scaling, and Linking

Abstract

Score equating is essential for any testing program that continually produces new editions of a test and for which the expectation is that scores from these editions have the same meaning over time. Different editions may be built to a common blueprint and designed to measure the same constructs, but they almost invariably differ somewhat in their psychometric properties. If one edition is more difficult than another, examinees would be expected to receive lower scores on the harder form. Score equating seeks to eliminate the effects on scores of these unintended differences in test form difficulty. Score equating is necessary to be fair to examinees and to provide score users with scores that mean the same thing across different editions or forms of the test.

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Notes

  1. 1.

    There are exceptions to this general case. For example, sometimes a multiple-choice anchor test is used to link two versions of an all constructed response test. Here the anchor score is more reliable than the scores to be equated. Although the characteristics of anchor tests are usually not specifically described in the requirements of equating or in summaries of these requirements, in practice linkings that utilize anchors that measure different constructs than the tests to be equated are considered unlikely to meet the requirements of equating.

  2. 2.

    Note that these subpopulations should not be defined on the basis of the tests to be equated or the anchor test, because the assumptions made by equating methods are sensitive to direct selection on the test or anchor, as demonstrated by Wright and Dorans (1993).

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Any opinions expressed in this chapter are those of the authors and not necessarily of Educational Testing Service.

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Correspondence to Neil J. Dorans .

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© 2009 Springer Science+Business Media, LLC

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Dorans, N.J., Moses, T.P., Eignor, D.R. (2009). Equating Test Scores: Toward Best Practices. In: von Davier, A. (eds) Statistical Models for Test Equating, Scaling, and Linking. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-98138-3_2

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