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Detecting Compromised Items Using Information From Secure Items

Author

Listed:
  • Xi Wang

    (Cognia)

  • Yang Liu

    (1068University of Maryland)

Abstract

In continuous testing programs, some items are repeatedly used across test administrations, and statistical methods are often used to evaluate whether items become compromised due to examinees’ preknowledge. In this study, we proposed a residual method to detect compromised items when a test can be partitioned into two subsets of items: secure items and possibly compromised items. We derived the standard error of the residual statistic by taking the sampling error in both ability and item parameter estimate into account. The simulation results suggest that the Type I error is close to the nominal level when both sources of error are adjusted, and item parameter error can be ignored only when the item calibration sample size is much larger than the evaluation sample size. We also investigated the performance of the residual method when not using information from secure items in both simulation and real data analyses.

Suggested Citation

  • Xi Wang & Yang Liu, 2020. "Detecting Compromised Items Using Information From Secure Items," Journal of Educational and Behavioral Statistics, , vol. 45(6), pages 667-689, December.
  • Handle: RePEc:sae:jedbes:v:45:y:2020:i:6:p:667-689
    DOI: 10.3102/1076998620912549
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    References listed on IDEAS

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    1. Zhan Shu & Robert Henson & Richard Luecht, 2013. "Using Deterministic, Gated Item Response Theory Model to Detect Test Cheating due to Item Compromise," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 481-497, July.
    2. Yang Liu & Ji Seung Yang & Alberto Maydeu-Olivares, 2019. "Restricted Recalibration of Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 529-553, June.
    3. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    4. Carol Woods & David Thissen, 2006. "Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 281-301, June.
    5. Carol M. Woods & David Thissen, 2006. "Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 281-301, June.
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    Cited by:

    1. Chen, Yunxiao & Lu, Yan & Moustaki, Irini, 2022. "Detection of two-way outliers in multivariate data and application to cheating detection in educational tests," LSE Research Online Documents on Economics 112499, London School of Economics and Political Science, LSE Library.
    2. Hyeon-Ah Kang, 2023. "Sequential Generalized Likelihood Ratio Tests for Online Item Monitoring," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 672-696, June.

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