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Measurement invariance testing in partial least squares structural equation modeling

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  • Dybro Liengaard, Benjamin

Abstract

When using structural equation modeling, comparison across time or groups can be misleading if measures are not invariant. Partial least squares structural equation modeling (PLS-SEM) is a method widely used in business research, but its ability to test for measurement invariance is limited. This study introduces a comprehensive approach for measurement invariance testing in reflective measurement models in PLS-SEM. The methodology diverges from the traditional measurement invariance of composite models (MICOM) approach and expands the possibilities of measurement invariance testing in three areas: 1) providing statistical tests to validate the comparison of latent means across groups; 2) measurement invariance testing in longitudinal studies; and 3) the ability to simultaneously assess measurement invariance across multiple groups. Additionally, this study proposes a strategy to address measurement invariance rejections in large-sample studies. The paper offers guidelines for the MI tests, and an empirical example illustrates their utility in facilitating experimental approaches in PLS-SEM.

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  • Dybro Liengaard, Benjamin, 2024. "Measurement invariance testing in partial least squares structural equation modeling," Journal of Business Research, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:jbrese:v:177:y:2024:i:c:s0148296324000857
    DOI: 10.1016/j.jbusres.2024.114581
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