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Tests of Matrix Structure for Construct Validation

Author

Listed:
  • Brian D. Segal

    (University of Michigan)

  • Thomas Braun

    (University of Michigan)

  • Richard Gonzalez

    (University of Michigan)

  • Michael R. Elliott

    (University of Michigan)

Abstract

Psychologists and other behavioral scientists are frequently interested in whether a questionnaire measures a latent construct. Attempts to address this issue are referred to as construct validation. We describe and extend nonparametric hypothesis testing procedures to assess matrix structures, which can be used for construct validation. These methods are based on a quadratic assignment framework and can be used either by themselves or to check the robustness of other methods. We investigate the performance of these matrix structure tests through simulations and demonstrate their use by analyzing a big five personality traits questionnaire administered as part of the Health and Retirement Study. We also derive rates of convergence for our overall test to better understand its behavior.

Suggested Citation

  • Brian D. Segal & Thomas Braun & Richard Gonzalez & Michael R. Elliott, 2019. "Tests of Matrix Structure for Construct Validation," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 65-83, March.
    • Handle: RePEc:spr:psycho:v:84:y:2019:i:1:d:10.1007_s11336-018-9647-4
    DOI: 10.1007/s11336-018-9647-4
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    References listed on IDEAS

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    4. R. Bock & Rolf Bargmann, 1966. "Analysis of covariance structures," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 507-534, December.
    5. R. McDonald, 1974. "Testing pattern hypotheses for covariance matrices," Psychometrika, Springer;The Psychometric Society, vol. 39(2), pages 189-201, June.
    6. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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