Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N.P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Cham: Springer.

 

 

 

 

 

 

 

Brief Description

 

 

 

Book Features

• This book is open access, which means that you have free and unlimited access

• Offers concise guidelines on how to apply and interpret PLS-SEM results

• Includes an illustrative step-by-step application of PLS-SEM within the R software environment

• Draws on the highly user-friendly SEMinR package, co-developed by two of the co-authors

• Adopts a case study approach that focuses on the illustration of relevant analysis steps

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3^rd ed. Thousand Oaks, CA: Sage.

All case studies in this PLS-SEM book use the SmartPLS 3 software.

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Brief Description

With applications using SmartPLS — the primary software used in partial least squares structural equation modeling (PLS-SEM) — this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the third edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

 

New to this edition

• All screenshots and instructions have been updated for the latest edition of the SmartPLS 3 software.
• The latest research on the nature of composite-based modeling provides a more thorough conceptual foundation for PLS-SEM.
• More on the distinction between PLS-SEM and CB-SEM helps readers choose the right technique for their project.
• Applications of PLS-SEM with secondary or archival data shows readers even more applications for this approach.
• Improved guidelines for generating and validating single-item measures for redundancy analyses and determining minimum sample sizes help clarify these steps.
• Coverage of model fit, analysis of predictive power, and metrics of model comparison have all been expanded for a richer discussion of PLS-SEM.
• A thoroughly revised and updated Chapter 7 on mediator and moderator analysis covers more types of mediation, and provides updated explanations and guidelines on moderated mediation.
• Extended coverage of more advanced concepts helps readers go further with PLS-SEM
• Summaries are now structured by learning outcome for improved organization.