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Person-level assessment of measurement invariance

Author

Listed:
  • Gregor Sočan

    (University of Ljubljana)

  • Gaja Zager Kocjan

    (University of Ljubljana)

Abstract

Existing procedures for testing measurement invariance focus mainly on group-level comparisons rather than individual comparisons (i.e., the main conclusion typically concerns the question of comparability of group means). We propose a set of intuitive graphical displays called Person-Level Assessment of Measurement Invariance (PLAMI), which attempt to provide information about the effect of the lack of measurement invariance on the level of person scores. This information complements the group-level information contained in model fit indices and overall effect size indices, and should be especially useful for practitioners using tests for individual diagnostics. PLAMI uses results from the multiple-group factor analysis to estimate and visualize score distortions in terms of expected score difference between members of different groups and the probability of an unacceptably high score difference, conditional for the value of latent trait. The stability of the results can be evaluated by means of resampling. Simulation can be used for an a priori evaluation of the sample size adequacy. We illustrate the proposed plots on two real examples involving testing measurement invariance of the Machiavellianism scale, and we demonstrate the added value of PLAMI compared to the use of fit indices alone.

Suggested Citation

  • Gregor Sočan & Gaja Zager Kocjan, 2022. "Person-level assessment of measurement invariance," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3481-3503, October.
    • Handle: RePEc:spr:qualqt:v:56:y:2022:i:5:d:10.1007_s11135-021-01262-z
    DOI: 10.1007/s11135-021-01262-z
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    References listed on IDEAS

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    4. Hao Wu & Ryne Estabrook, 2016. "Identification of Confirmatory Factor Analysis Models of Different Levels of Invariance for Ordered Categorical Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 1014-1045, December.
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