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

    A Workbook

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    Author(s)
    Hair Jr., Joseph F.
    Hult, G. Tomas M.
    Ringle, Christian M.
    Sarstedt, Marko
    Danks, Nicholas P.
    Ray, Soumya
    Language
    English
    Show full item record
    Abstract
    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.
    URI
    https://library.oapen.org/handle/20.500.12657/51463
    Keywords
    Open Access; PLS-SEM) Using R; Workbook; Partial Least Squares Structural Equation Modeling; R Software Environment
    DOI
    10.1007/978-3-030-80519-7
    ISBN
    9783030805197, 9783030805197
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    2021
    Grantor
    • Otto von Guericke University Magdeburg - [grantnumber unknown]
    Imprint
    Springer International Publishing
    Series
    Classroom Companion: Business,
    Classification
    Sales and marketing
    Mathematical and statistical software
    Econometrics and economic statistics
    Pages
    197
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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