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Applying Multigroup Analysis in PLS-SEM: A Step-by-Step Process

In: Partial Least Squares Path Modeling

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  • Lucy Matthews

    (Middle Tennessee State University)

Abstract

This book chapter identifies the importance and different uses for multigroup analysis, such as research interests in cross-cultural or gender differences. Multigroup analysis via partial least squares structural equations modeling, which tests a single structural relationship at a time, is an effective way to evaluate moderation across multiple relationships versus standard moderation. Step-by-step instructions and guidelines using SmartPLS 3.0 are provided using a sample dataset. The instructions include an assessment of the measurement characteristics of the constructs by including the MICOM procedure, which adds an additional level of accuracy. Examples of both positive and negative outcomes as well as potential solutions to problems are provided in order to help users understand how to apply multigroup analysis to their own dataset. By using multigroup analysis, researchers are able to uncover differences of subsamples within the total population that is not evident when examined as a whole. Researchers having the ability to run multigroup analysis considerably improve the likelihood of identifying significant and meaningful differences in various relationships across group-specific results.

Suggested Citation

  • Lucy Matthews, 2017. "Applying Multigroup Analysis in PLS-SEM: A Step-by-Step Process," Springer Books, in: Hengky Latan & Richard Noonan (ed.), Partial Least Squares Path Modeling, chapter 0, pages 219-243, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-64069-3_10
    DOI: 10.1007/978-3-319-64069-3_10
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    Cited by:

    1. Hanafiah Hasin & Siti Fatimah Noor & Rahayu Mohd Sehat & Zaleha Mahat & Muhammad Arif Hakimy Syamsul Kahar & Anita Jamil, 2025. "A Conceptual Framework for a Cross-National Study on Fintech Adoption and Financial Literacy among Students in Malaysia and Indonesia," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(10), pages 279-287, October.

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