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April 26, 2026Open Access

Consistent partial least squares structural equation modeling using SmartPLS

JCJun Hwa Cheah MSMarko Sarstedt JHJoseph F. Hair

Key Points

The aim is to illustrate consistent partial least squares structural equation modeling (PLSc-SEM) and its advantages over traditional methods.
Illustration of PLSc-SEM using SmartPLS 4 software.
Comparison of PLSc-SEM results with covariance-based SEM using maximum likelihood estimation.
Demonstration of model setup and interpretation in the software.
PLSc-SEM provides corrected construct correlations for better estimation of common factor models.
Results contrast favorably with covariance-based SEM, enhancing model reliability.

Abstract

This Teacher’s Corner article provides a comprehensive illustration of consistent partial least squares structural equation modeling (PLSc-SEM), a variant of the original PLS-SEM method, which corrects construct correlations for attenuation. The method thereby allows estimating common factor models within a composite-based SEM framework. Our descriptions draw on SmartPLS 4, the most frequently used software for conducting PLS-SEM analyses, illustrating how to set up and estimate the model and interpret the estimates. We further contrast our results with those from other composite-based SEM estimators and from covariance-based SEM using maximum likelihood estimation, as implemented in SmartPLS.

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