Partial least squares structural equation modeling (PLS-SEM) using R: a workbook

By:

Hair, Joseph F

Contributor(s):

Material type: Text

TextPublication details: Springer Switzerland 2021Description: xiv, 197 pISBN:

9783030805180

Subject(s):

DDC classification:

511.42 HAI

Summary: About this book 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.

List(s) this item appears in: Operation & quantitative Techniques | IT & Decision Sciences

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	511.42 HAI (Browse shelf(Opens below))	1	Available		002846

About this book
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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