A primer on partial least squares structural equation modeling (PLS-SEM)
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Bibliographic Information
A primer on partial least squares structural equation modeling (PLS-SEM)
Sage, c2017
2nd ed
- : pbk
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Other authors: G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt
Includes bibliographical references (p. 331-345) and indexes
Description and Table of Contents
Description
With applications using SmartPLS -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.
Please note that all examples in this Second Edition use SmartPLS 3. To access this software, please visit
Table of Contents
Chapter 1: An Introduction to Structural Equation Modeling
What Is Structural Equation Modeling?
Considerations in Using Structural Equation Modeling
Structural Equation Modeling With Partial Least Squares Path Modeling
PLS-SEM, CB-SEM, and Regressions Based on Sum Scores
Organization of Remaining Chapters
Chapter 2: Specifying the Path Model and Examining Data
Stage 1: Specifying the Structural Model
Stage 2: Specifying the Measurement Models
Stage 3: Data Collection and Examination
Case Study Illustration: Specifying the PLS-SEM Model
Path Model Creation Using the SmartPLS Software
Chapter 3: Path Model Estimation
Stage 4: Model Estimation and the PLS-SEM Algorithm
Case Study Illustration: PLS Path Model Estimation (Stage 4)
Chapter 4: Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models
Overview of Stage 5: Evaluation of Measurement Models
Stage 5a: Assessing Results of Reflective Measurement Models
Case Study Illustration-Reflective Measurement Models
Running the PLS-SEM Algorithm
Reflective Measurement Model Evaluation
Chapter 5: Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models
Stage 5b: Assessing Results of Formative Measurement Models
Bootstrapping Procedure
Bootstrap Confidence Intervals
Case Study Illustration-Evaluation of Formative Measurement Models
Chapter 6: Assessing PLS-SEM Results Part III: Evaluation of the Structural Model
Stage 6: Assessing PLS-SEM Structural Model Results
Case Study Illustration-How Are PLS-SEM Structural Model Results Reported?
Chapter 7: Mediator and Moderator Analysis
Mediation
Moderation
Chapter 8: Outlook on Advanced Methods
Importance-Performance Map Analysis
Hierarchical Component Models
Confirmatory Tetrad Analysis
Dealing With Observed and Unobserved Heterogeneity
Consistent Partial Least Squares
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