Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R : A Workbook / by Joseph F Hair Jr, G Tomas M Hult, Christian M Ringle, Marko Sarstedt, Nicholas P Danks, Soumya Ray
Por: Hair Jr., Joseph F, autor..
Series (Classroom Companion: Business, 2662-2874).Editor: Cham : Springer International Publishing, 2021Edición: 1st ed. 2021.Descripción: 1 recurso en línea.ISBN: 9783030805197.Recursos en línea: Acceso a este recurso digital (usuarios Universidad Europea de Valencia)
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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.
Open Access
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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