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Comparison of Two Item Preknowledge Detection Approaches Using Response Time

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Quantitative Psychology (IMPS 2017, IMPS 2018)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 265))

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Abstract

Response time (RT) has been demonstrated to be effective in identifying compromised items and test takers with item preknowledge. This study compared the performance of the effective response time (ERT) approach and the residual based on the lognormal response time model (RES) approach in detecting the examinees with item preknowledge using item response time in a linear test. Three factors were considered in this study: the percentage of examinees with item preknowledge, the percentage of breached items, and the percent decrease of response time of the breached items. The results suggest that the RES approach not only controls the Type I error rate below 0.05 for all investigated conditions, but also flag the examinees with item preknowledge sensitively.

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Author information

Authors and Affiliations

  1. National Board of Medical Examiners®, Philadelphia, PA, 19104, USA

    Chunyan Liu

Authors
  1. Chunyan Liu
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Corresponding author

Correspondence to Chunyan Liu .

Editor information

Editors and Affiliations

  1. Department of Statistics, UmeĂĄ School of Business, Economics and Statistics, UmeĂĄ University, UmeĂĄ, Sweden

    Marie Wiberg

  2. Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL, USA

    Steven Culpepper

  3. Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium

    Rianne Janssen

  4. Facultad de Matematicas, Pontificia Universidad Catolica de Chile, Santiago, Chile

    Jorge González

  5. Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands

    Dylan Molenaar

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Liu, C. (2019). Comparison of Two Item Preknowledge Detection Approaches Using Response Time. In: Wiberg, M., Culpepper, S., Janssen, R., González, J., Molenaar, D. (eds) Quantitative Psychology. IMPS IMPS 2017 2018. Springer Proceedings in Mathematics & Statistics, vol 265. Springer, Cham. https://doi.org/10.1007/978-3-030-01310-3_31

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