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This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications.
List of contents
Part I Preliminaries and Basic Methods
1. Framing Structural Equation Modelling
2. Multivariate Statistics Prerequisites
3. PLS Structural Equation Modelling: Specification and Estimation
4. PLS Structural Equation Modelling: Assessment and Interpretation
Part II Advanced Methods
5. Mediation AnalysisWith PLS-SEM
6. Moderating/Interaction Effects Using PLS-SEM
7. Detecting Unobserved Heterogeneity in PLS-SEM
Part III Conclusions
8. How to Write Up a PLS-SEM Study
Part IV Appendices
A. Basic Statistics Prerequisites
About the author
Mehmet Mehmetoglu is a professor of research methods in the Department of Psychology at the Norwegian University of Science and Technology (NTNU). His research interests include consumer psychology, evolutionary psychology and statistical methods. Mehmetoglu has co/publications in about 30 different refereed international journals such as Journal of Statistical Software, Personality and Individual Differences, and Evolutionary Psychological Science.
Sergio Venturini is an Associate Professor of Statistics in the Management Department at the Università degli Studi di Torino (Italy). His research interests include Bayesian data analysis methods, meta-analysis and statistical computing. He coauthored many publications that have been published in different refereed international journals such as Annals of Applied Statistics, Bayesian Analysis and Journal of Statistical Software.
Summary
This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications.
Additional text
"...This is certainly a welcome addition to the capability of Stata, and moreover, this book also includes sections on the use of packages in R software for PLS structural equation modeling...this book takes a balanced approach to presenting the statistical theory of PLS structural equationmodeling and its practical applications. The mathematical level is not high but is higher thanmost books on PLS structural equation modeling...this book will be useful for users of other software with an interest in getting a grasp of statistical theory behind PLS structural equation modeling. It is comprehensive and also accessible. Anyone who is seriously thinking of using PLS structural equation modeling for their research should carefully read through this book before embarking on their first analysis."- Yu-Kang Tu, Biometrics, July 2021
