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

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�...

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Päätekijä: Hair Jr., Joseph F. (auth)
Muut tekijät: Hult, G. Tomas M. (auth), Ringle, Christian M. (auth), Sarstedt, Marko (auth), Danks, Nicholas P. (auth), Ray, Soumya (auth)
Aineistotyyppi: Elektroninen Kirjan osa
Kieli:englanti
Julkaistu: Springer Nature 2021
Sarja:Classroom Companion: Business
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Yhteenveto: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.
Ulkoasu:1 electronic resource (197 p.)
ISBN:978-3-030-80519-7
9783030805197
Pääsy:Open Access