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Numerous statistical methods are available for social researchers. Therefore, knowing the appropriate technique can be a challenge. For example, when considering structural equation modelling (SEM), selecting between covariance-based (CB-SEM) and variance-based partial least squares (PLS-SEM) can be challenging. This paper applies the same theoretical measurement and structural models and dataset to conduct a direct comparison. The findings reveal that when using CB-SEM, many indicators are removed to achieve acceptable goodness-of-fit, when compared to PLS-SEM. Also, composite reliability and convergent validity were typically higher using PLS-SEM, but other metrics such as discriminant validity and beta coefficients are comparable. Finally, when comparing variance explained in the dependent variable indicators, PLS-SEM was substantially better than CB-SEM. Updated guidelines assist researchers in determining whether CB-SEM or PLS-SEM is the most appropriate method to use.
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Joe F. Hair
Lucy M. Matthews
Ryan Matthews
International Journal of Multivariate Data Analysis
University of Newcastle Australia
Otto-von-Guericke University Magdeburg
University of South Alabama
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Hair et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69d738d78e958094d1b8a4d5 — DOI: https://doi.org/10.1504/ijmda.2017.087624