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

Edison M. Choe, Hua Hua Chang

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1129-1151
Number of pages23
JournalPsychometrika
Volume84
Issue number4
DOIs
StatePublished - Dec 1 2019
Externally publishedYes

Keywords

  • asymptotic theory
  • computerized adaptive testing
  • item exposure
  • pool utilization
  • test overlap
  • test security

ASJC Scopus subject areas

  • General Psychology
  • Applied Mathematics

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