 Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendationsJun-Hwa Cheah, Suzanne Amaro and José L. Roldán Journal of Business Research, 2023, vol. 156, issue C Abstract: Multigroup analysis (MGA) in partial least squares structural equation modeling (PLS-SEM) has grown considerably in the past few years in many different research fields, particularly in the business area. However, a close examination of MGA in PLS-SEM articles revealed much less research that compared more than two groups. Furthermore, research applying MGA in PLS-SEM with more than two groups has several constraints. For instance, most researchers need clarification about using either the omnibus test of group differences (OTG) or non-parametric distance-based tests (NDT) for an overall difference across the groups. Moreover, they do not handle family-wise error when comparing more than two groups, nor do they check for measurement invariance. This article uses an empirical illustration to fully understand multigroup analysis with more than two groups, providing valuable guidelines and comprehensible recommendations for researchers applying PLS-MGA. Keywords: Multigroup Analysis; Group Comparison; Non-parametric Distance-Based Test; Non-parametric Permutation-Based Test; Omnibus Test Group Differences; Partial Least Squares Structural Equation Modeling (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:156:y:2023:i:c:s0148296322010049 DOI: 10.1016/j.jbusres.2022.113539 Access Statistics for this article Journal of Business Research is currently edited by A. G. Woodside More articles in Journal of Business Research from Elsevier |
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