The Asymptotic Distribution of Average Test Overlap Rate in Computerized Adaptive Testing

Edison M. Choe () and Hua-Hua Chang ()
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Edison M. Choe: Graduate Management Admission Council™ (GMAC™)
Hua-Hua Chang: Purdue University

Psychometrika, 2019, vol. 84, issue 4, No 11, 1129-1151

Abstract: Abstract The average test overlap rate is often computed and reported as a measure of test security risk or item pool utilization of a computerized adaptive test (CAT). Despite the prevalent use of this sample statistic in both literature and operations, its sampling distribution has never been known nor studied in earnest. In response, a proof is presented for the asymptotic distribution of a linear transformation of the average test overlap rate in fixed-length CAT. The theoretical results enable the estimation of standard error and construction of confidence intervals. Moreover, a practical simulation study demonstrates the statistical comparison of average test overlap rates between two CAT designs with different exposure control methods.

Keywords: test overlap; item exposure; test security; pool utilization; computerized adaptive testing; asymptotic theory (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11336-019-09674-5

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