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Partial least squares structural equ...

Hair, Joseph F.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Partial least squares structural equation modeling (PLS-SEM) using R/ by Joseph F. Hair Jr. ...[et al.].
Reminder of title:	a workbook /
other author:	Hair, Joseph F.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xiv, 197 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Least squares. -
Online resource:	https://doi.org/10.1007/978-3-030-80519-7
ISBN:	9783030805197

Partial least squares structural equation modeling (PLS-SEM) using R = a workbook /
Partial least squares structural equation modeling (PLS-SEM) using Ra workbook /[electronic resource] :by Joseph F. Hair Jr. ...[et al.]. - Cham :Springer International Publishing :2021. - xiv, 197 p. :ill. (some col.), digital ;24 cm. - Classroom companion: business,2662-2874. - Classroom companion: business..

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.

ISBN: 9783030805197

Standard No.: 10.1007/978-3-030-80519-7doiSubjects--Topical Terms:

549973
Least squares.

LC Class. No.: QA275

Dewey Class. No.: 511.42

Partial least squares structural equation modeling (PLS-SEM) using R = a workbook /
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505 0 $a 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.
506 0 $a Open Access
520 $a 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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