Measurement invariance testing in partial least squares structural equation modeling

Benjamin Dybro Liengaard

Journal of Business Research, 2024, vol. 177, issue C

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.

Keywords: Structural equation modeling; Measurement; Measurement invariance; Partial least squares; Longitudinal; Multigroup analysis (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:177:y:2024:i:c:s0148296324000857

DOI: 10.1016/j.jbusres.2024.114581

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