Partial Least Squares Structural Equation Modeling PLS SEM Using R
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- Author : Joseph F. Hair Jr.
- Publisher : Springer Nature
- Release : 03 November 2021
- ISBN : 9783030805197
- Page : 197 pages
- Rating : 4.5/5 from 103 voters
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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 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
- Author : Joseph F. Hair Jr.,G. Tomas M. Hult,Christian M. Ringle,Marko Sarstedt,Nicholas P. Danks,Soumya Ray
- Publisher : Springer Nature
- Release Date : 2021-11-03
- ISBN : 9783030805197
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
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
- Author : Joseph F. Hair Jr.,G. Tomas M. Hult,Christian M. Ringle,Marko Sarstedt,Nicholas P. Danks,Soumya Ray
- Publisher : Springer
- Release Date : 2021-11-04
- ISBN : 3030805182
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
Partial Least Squares Structural Equation Modeling
- Author : Necmi K. Avkiran,Christian M. Ringle
- Publisher : Springer
- Release Date : 2018-02-16
- ISBN : 9783319716916
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 in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena
Structural Equation Modelling with Partial Least Squares Using Stata and R
- Author : Mehmet Mehmetoglu,Sergio Venturini
- Publisher : CRC Press
- Release Date : 2020-12-22
- ISBN : 9780429528859
Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)
- Author : Joseph F. Hair, Jr.,G. Tomas M. Hult,Christian Ringle,Marko Sarstedt
- Publisher : SAGE Publications
- Release Date : 2016-02-29
- ISBN : 9781483377438
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt is a practical guide that provides concise instructions on how to use partial least squares structural equation modeling (PLS-SEM), an evolving statistical technique, to conduct research and obtain solutions. Featuring the latest research, new examples using the SmartPLS software, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited
Partial Least Squares Path Modeling
- Author : Hengky Latan,Richard Noonan
- Publisher : Springer
- Release Date : 2017-11-03
- ISBN : 9783319640693
This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-PM. The first section of this book emphasizes the basic concepts and extensions of the PLS-PM method. The second section discusses the methodological issues that are the focus of the recent development of the PLS-PM method. The third part discusses the real world application of the PLS-PM method in various disciplines.
Mastering Partial Least Squares Structural Equation Modeling (Pls-Sem) with Smartpls in 38 Hours
- Author : Ken Kwong-Kay Wong
- Publisher : iUniverse
- Release Date : 2019-02-22
- ISBN : 9781532066481
Partial least squares is a new approach in structural equation modeling that can pay dividends when theory is scarce, correct model specifications are uncertain, and predictive accuracy is paramount. Marketers can use PLS to build models that measure latent variables such as socioeconomic status, perceived quality, satisfaction, brand attitude, buying intention, and customer loyalty. When applied correctly, PLS can be a great alternative to existing covariance-based SEM approaches. Dr. Ken Kwong-Kay Wong wrote this reference guide with graduate students and
Partial Least Squares Path Modeling of Latent Variables
- Author : Vincenzo Esposito Vinzi,Mehmet Mehmetoglu
- Publisher : Chapman and Hall/CRC
- Release Date : 2017-06-26
- ISBN : 1482227819
Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods
Advanced Issues in Partial Least Squares Structural Equation Modeling
- Author : Joseph F. Hair, Jr.,Marko Sarstedt,Christian M. Ringle,Siegfried P. Gudergan
- Publisher : SAGE Publications
- Release Date : 2017-04-05
- ISBN : 9781483377414
Written as an extension of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Second Edition, this easy-to-understand, practical guide covers advanced content on PLS-SEM to help students and researchers apply techniques to research problems and accurately interpret results. The book provides a brief overview of basic concepts before moving to the more advanced material. Offering extensive examples on SmartPLS 3 software (www.smartpls.com) and accompanied by free downloadable data sets, the book emphasizes that any advanced PLS-SEM approach
Composite-Based Structural Equation Modeling
- Author : Jörg Henseler
- Publisher : Guilford Publications
- Release Date : 2020-12-24
- ISBN : 9781462545612
This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Jörg Henseler introduces the types of research questions that can be addressed with composite-based SEM and explores the differences between composite- and factor-based SEM, variance- and covariance-based SEM, and emergent and latent variables. Using rich illustrations and walked-through data sets, the book covers how to specify, identify, estimate, and assess composite models using partial least squares path modeling, maximum
Handbook of Partial Least Squares
- Author : Vincenzo Esposito Vinzi,Wynne W. Chin,Jörg Henseler,Huiwen Wang
- Publisher : Springer Science & Business Media
- Release Date : 2010-03-10
- ISBN : 9783540328278
This handbook provides a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing and with a discussion of the directions of current research and perspectives. It covers the broad area of PLS methods, from regression to structural equation modeling applications, software and interpretation of results. The handbook serves both as an introduction for those without prior knowledge of PLS and as a comprehensive reference for researchers and practitioners interested in the most recent
Discovering Partial Least Squares with JMP
- Author : Ian Cox,Marie Gaudard
- Publisher : SAS Institute
- Release Date : 2013-10
- ISBN : 9781629590929
Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores Partial Least Squares and positions it within the more general context of multivariate analysis. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.
Structural Equation Models
- Author : J. Christopher Westland
- Publisher : Springer
- Release Date : 2015-04-25
- ISBN : 9783319165073
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that
New Challenges to International Marketing
- Author : Tamer Cavusgil,Rudolf R. Sinkovics,Pervez N. Ghauri
- Publisher : Emerald Group Publishing
- Release Date : 2009-02-20
- ISBN : 9781848554696
Addresses the impact on international marketing of major trends in the external and internal environment of the firm: technology-enabled international marketing research, global account management, procurement and international supplier networks, internationalization of small and entrepreneurial firms, and outsourcing and offshoring.
Latent Variable Path Modeling with Partial Least Squares
- Author : Jan-Bernd Lohmöller
- Publisher : Springer Science & Business Media
- Release Date : 2013-11-11
- ISBN : 9783642525124
Partial Least Squares (PLS) is an estimation method and an algorithm for latent variable path (LVP) models. PLS is a component technique and estimates the latent variables as weighted aggregates. The implications of this choice are considered and compared to covariance structure techniques like LISREL, COSAN and EQS. The properties of special cases of PLS (regression, factor scores, structural equations, principal components, canonical correlation, hierarchical components, correspondence analysis, three-mode path and component analysis) are examined step by step and contribute