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

• Main Authors: Hair Jr., Joseph F. (Author), Hult, G. Tomas M. (Author), Ringle, Christian M. (Author), Sarstedt, Marko (Author), Danks, Nicholas P. (Author), Ray, Soumya (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
• Edition: 1st ed. 2021.
• Series: Classroom Companion: Business,
• Subjects: Marketing.; Statistics > Computer programs.; Econometrics.; Statistical Software.
• Online Access: Link to Metadata

Summary

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 of thumbin every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

Physical Description

XIV, 197 p. 77 illus., 51 illus. in color. online resource.

ISBN

9783030805197

ISSN

2662-2874

DOI

10.1007/978-3-030-80519-7

Access

Open Access