Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook

An Introduction to Structural Equation Modeling.- Introduction to R and RStudio.- Introduction to SEMinR.- Evaluation of Reflective Measurement Models.- Evaluation of Formative Measurement Models.- Evaluation of the Structural Model.- Mediation Analysis.- Moderation Analysis. Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules ofthumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

• | Author: Christian M. Ringle, Soumya Ray, Nicholas P. Danks, Marko Sarstedt, Joseph F. Hair Jr., G. Tomas M. Hult
• | Publisher: Springer Nature Switzerland AG
• | Publication Date: Nov 04, 2021
• | Number of Pages:
• | Language:
• | Binding: Hardback
• | ISBN-13: 9783030805180
• | ISBN-10: 3030805182