A primer on partial least squares structural equation modeling (PLS-SEM) /
General Material Designation
[Book]
First Statement of Responsibility
Joseph F. Hair, Jr., Kennesaw State University, G. Tomas M. Hult, Christian M Ringle, Marko Sarstedt.
EDITION STATEMENT
Edition Statement
Second edition.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Los Angeles :
Name of Publisher, Distributor, etc.
Sage,
Date of Publication, Distribution, etc.
[2017]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xx, 363 pages ;
Dimensions
23 cm
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
An introduction to structural equation modeling -- Specifying the path model and examining data -- Path model estimation -- Assessing PLS-SEM results part I: evaluation of reflective measurement models -- Assessing PLS-SEM results part II: evaluation of the formative measurement models -- Assessing PLS-SEM results part III: evaluation of the structural model -- Mediator and moderator analysis -- Outlook on advanced methods.
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SUMMARY OR ABSTRACT
Text of Note
With applications using SmartPLS (www.smartpls.com) - the primary software used in partial least squares structural equation modeling (PLS-SEM) - this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways -- page 4 of cover.