Actions for A primer on partial least squares structural equation modeling (PLS-SEM)
A primer on partial least squares structural equation modeling (PLS-SEM) / Joseph F. Hair, Jr. [and others].
- Published
- Thousand Oaks, Calif. : SAGE Publications, [2014]
- Copyright Date
- ©2014
- Physical Description
- xvi, 307 pages : illustrations ; 23 cm
- Additional Creators
- Hair, Joseph F.
- Contents
- Machine generated contents note: ch. 1 An Introduction to Structural Equation Modeling -- Learning Outcomes -- Chapter Preview -- What Is Structural Equation Modeling? -- Considerations in Using Structural Equation Modeling -- The Variate -- Measurement -- Measurement Scales -- Coding -- Data Distributions -- Structural Equation Modeling With Partial Least Squares Path Modeling -- Path Models With Latent Variables -- Measurement Theory -- Structural Theory -- PLS-SEM and CB-SEM -- Data Characteristics -- Model Characteristics -- Organization of Remaining Chapters -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 2 Specifying the Path Model and Collecting Data -- Learning Outcomes -- Chapter Preview -- Stage 1 Specifying the Structural Model -- Mediation -- Moderation -- Higher-Order and Hierarchical Component Models -- Stage 2 Specifying the Measurement Models -- Reflective and Formative Measurement Models -- Single-Item Measures -- Stage 3 Data Collection and Examination -- Missing Data -- Suspicious Response Patterns -- Outliers -- Data Distribution -- Case Study Illustration: Specifying the PLS-SEM Model -- Application of Stage 1 Structural Model Specification -- Application of Stage 2 Measurement Model Specification -- Application of Stage 3 Data Collection and Examination -- Path Model Creation Using the SmartPLS Software -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 3 Path Model Estimation -- Learning Outcomes -- Chapter Preview -- Stage 4 Model Estimation and the PLS-SEM Algorithm -- How the Algorithm Works -- Statistical Properties -- Algorithmic Options and Parameter Settings to Run the Algorithm -- Results -- Case Study Illustration: PLS Path Model Estimation (Stage 4) -- Model Estimation -- Estimation Results -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 4 Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models -- Learning Outcomes -- Chapter Preview -- Overview of Stage 5 Evaluation of Measurement Models -- Stage 5a Assessing Results of Reflective Measurement Models -- Internal Consistency Reliability -- Convergent Validity -- Discriminant Validity -- Case Study Illustration---Reflective Measurement Models -- Running the PLS-SEM Algorithm -- Reflective Measurement Model Evaluation -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 5 Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models -- Learning Outcomes -- Chapter Preview -- Stage 5b Assessing Results of Formative Measurement Models -- Step 1 Assess Convergent Validity -- Step 2 Assess Formative Measurement Models for Collinearity Issues -- Step 3 Assess the Significance and Relevance of the Formative Indicators -- Bootstrapping Procedure -- Concept and Justification -- Bootstrap Confidence Intervals -- Case Study Illustration---Evaluation of Formative Measurement Models -- Extending the Simple Path Model -- Reflective Measurement Model Evaluation -- Formative Measurement Model Evaluation -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 6 Assessing PLS-SEM Results Part III: Evaluation of the Structural Model -- Learning Outcomes -- Chapter Preview -- Stage 6 Assessing PLS-SEM Structural Model Results -- Step 1 Collinearity Assessment -- Step 2 Structural Model Path Coefficients -- Step 3 Coefficient of Determination (R2 Value) -- Step 4 Effect Size f2 -- Step 5 Blindfolding and Predictive Relevance Q2 -- Heterogeneity -- Goodness-of-Fit Index -- Case Study Illustration: How Are PLS-SEM Structural Model Results Reported? -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 7 Advanced Topics in PLS-SEM -- Learning Outcomes -- Chapter Preview -- Importance-Performance Matrix Analysis -- Method -- Case Study Illustration -- Mediator Analysis -- Method -- Case Study Illustration -- Higher-Order Models/Hierarchical Component Models -- Method -- Case Study Illustration -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings -- ch. 8 Modeling Heterogeneous Data -- Learning Outcomes -- Chapter Preview -- Modeling Categorical Moderator Effects -- Introduction -- The Parametric Approach to PLS-MGA -- Measurement Invariance -- Case Study Illustration -- Modeling Unobserved Heterogeneity -- Continuous Moderator Effects -- Method -- Modeling Continuous Moderating Effects -- Three-Way Interactions -- Creating the Interaction Term -- Case Study Illustration -- Summary -- Review Questions -- Critical Thinking Questions -- Key Terms -- Suggested Readings.
- Subject(s)
- ISBN
- 9781452217444 (pbk.)
1452217440 (pbk.) - Bibliography Note
- Includes bibliographical references and indexes.
- Source of Acquisition
- Altoona copy: Selected to honor Tulay Girard, on the occasion of receiving promotion; and purchased with funds from the Paterno Libraries Endowment; 2015.
- Endowment Note
- Paterno Libraries Endowment
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