Partial Least Squares Structural Equation Modeling

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

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
Author :
Publisher : Springer Nature
Total Pages : 208
Release :
ISBN-10 : 9783030805197
ISBN-13 : 3030805190
Rating : 4/5 (190 Downloads)

Book Synopsis Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R by : Joseph F. Hair Jr.

Download or read book Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R written by Joseph F. Hair Jr. and published by Springer Nature. This book was released on 2021-11-03 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R Related Books

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
Language: en
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Authors: Joseph F. Hair Jr.
Categories: Business & Economics
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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 laten
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This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used