Statistics

Multivariate statistics

Data mining

Computer science

Statistical analysis

Structural equation modeling

Mathematics

Partial least squares regression

Machine learning

Journal of Applied Structural Equation Modeling

Partial least squares structural equation modeling (PLS-SEM) is one of the most widely used methods of multivariate data analysis. Although previous research has discussed different aspects of PLS-SEM, little has been done to explain the attributes of the various PLS-SEM statistical applications. The objective of this editorial is to discuss the multiple PLS-SEM applications, including SmartPLS, WarpPLS, and ADANCO. It is written based on information received from the developers via emails as well as our ongoing understanding and experience of using these applications. We hope this editorial will serve as a manual for users to understand the unique characteristics of each PLS-SEM application and make informed decisions on the most appropriate application for their research.

PLS-SEM STATISTICAL PROGRAMS: A REVIEW