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Test designs and modeling under the general nominal diagnosis model framework

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  • Jinsong Chen
  • Hui Zhou

Abstract

Most psychological questionnaires face issues of response bias in respondent-reported scales, inadequacy for criterion-reference testing, or difficulty in estimating a large number of latent traits. Situational tests together with the general nominal diagnosis model framework provide a viable alternative to alleviate these concerns. Under this framework, there are different ways to design situationally nominal items, which can offer more flexibility for test development. Any response bias remaining with respondent-reported questionnaires may be addressed with appropriate test designs. The saturated model subsumes different reduced forms that can help inform whether the test is designed as expected. Two simulation studies are presented to demonstrate the effectiveness of the models and designs.

Suggested Citation

  • Jinsong Chen & Hui Zhou, 2017. "Test designs and modeling under the general nominal diagnosis model framework," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-14, June.
  • Handle: RePEc:plo:pone00:0180016
    DOI: 10.1371/journal.pone.0180016
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    Cited by:

    1. Luca Stefanutti & Debora Chiusole & Pasquale Anselmi & Andrea Spoto, 2020. "Extending the Basic Local Independence Model to Polytomous Data," Psychometrika, Springer;The Psychometric Society, vol. 85(3), pages 684-715, September.

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