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Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
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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.
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Keywords
- Business & management
- Business applications
- Computing & information technology
- Econometrics
- Economics
- Economics, finance, business & management
- Mathematical & Statistical Software
- open access
- Partial Least Squares Structural Equation Modeling
- PLS-SEM) Using R
- R Software Environment
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- Workbook
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DOI: 10.1007/978-3-030-80519-7Editions