Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
A Workbook
Author(s)
Hair Jr., Joseph F.
Hult, G. Tomas M.
Ringle, Christian M.
Sarstedt, Marko
Danks, Nicholas P.
Ray, Soumya
Language
EnglishAbstract
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 thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.
Keywords
Open Access; PLS-SEM) Using R; Workbook; Partial Least Squares Structural Equation Modeling; R Software EnvironmentDOI
10.1007/978-3-030-80519-7ISBN
9783030805197, 9783030805197Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
2021Imprint
Springer International PublishingSeries
Classroom Companion: Business,Classification
Sales and marketing
Mathematical and statistical software
Econometrics and economic statistics