A primer on partial least squares structural equations modeling (PLS-SEM)
- 3rd
- Los Angeles Sage Publications, Inc. 2021
- xx, 363 p.
Table of content Preface About the Authors Chapter 1. An Introduction to Structural Equation Modeling Chapter Preview What Is Structural Equation Modeling? Considerations in Using Structural Equation Modeling Principles of Structural Equation Modeling PLS-SEM, CB-SEM, and Regressions Based on Sum Scores Considerations When Applying PLS-SEM Guidelines for Choosing Between PLS-SEM and CB-SEM Organization of Remaining Chapters Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 2. Specifying the Path Model and Examining Data Chapter Preview Stage 1: Specifying the Structural Model Stage 2: Specifying the Measurement Models Stage 3: Data Collection and Examination Case Study Illustration-Specifying the PLS-SEM Model Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 3. Path Model Estimation Chapter Preview Stage 4: Model Estimation and the PLS-SEM Algorithm Case Study Illustration-PLS Path Model Estimation (Stage 4) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 4. Assessing PLS-SEM Results-Part I: Evaluation of the Reflective Measurement Models Chapter Preview Overview of Stage 5: Evaluation of Measurement Models Stage 5a: Assessing Results of Reflective Measurement Models Case Study Illustration-Evaluation of the Reflective Measurement Models (Stage 5a) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 5. Assessing PLS-SEM Results-Part II: Evaluation of the Formative Measurement Models Chapter Preview Stage 5b: Assessing Results of Formative Measurement Models Case Study Illustration-Evaluation of the Formative Measurement Models (Stage 5b) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 6. Assessing PLS-SEM Results-Part III: Evaluation of the Structural Model Chapter Preview Stage 6: Structural Model Results Evaluation Case Study Illustration-Evaluation of the Structural Model (Stage 6) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 7. Mediator and Moderator Analysis Chapter Preview Mediation Moderation Case Study Illustration-Moderation Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 8. Outlook on Advanced Methods Chapter Preview Importance-Performance Map Analysis Necessary Condition Analysis Higher-Order Constructs Confirmatory Tetrad Analysis Examining Endogeneity Treating Observed and Unobserved Heterogeneity Measurement Model Invariance Consistent PLS-SEM Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Glossary References Index Purchasing options Please select a format: Paperback ISBN: 9781544396408 $45.00 Order from: Buy from SAGE Amazon FlipKart Related Products Advanced Issues in Partial Least Squares Structural Equation Modeling Advanced Issues in Partial Least Squares Structural Equation Modeling
The third edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering the techniques of this approach in clear language. Authors Joseph H. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt use their years of conducting and teaching research to communicate the fundamentals of PLS-SEM in straightforward language to explain the details of this method, with limited emphasis on equations and symbols. A running case study on corporate reputation follows the different steps in this technique so readers can better understand the research applications. Learning objectives, review and critical thinking questions, and key terms help readers cement their knowledge. This edition has been thoroughly updated, featuring the latest version of the popular software package SmartPLS 3. New topics have been added throughout the text, including a thoroughly revised and extended chapter on mediation, recent research on the foundations of PLS-SEM, detailed descriptions of research summarizing the advantages as well as limitations of PLS-SEM, and extended coverage of advanced concepts and methods, such as out-of-sample versus in-sample prediction metrics, higher-order constructs, multigroup analysis, necessary condition analysis, and endogeneity.