Chapter 1 • An Introduction to Structural Equation Modeling

• Chapter Preview
• What Is Structural Equation Modeling?
• Considerations in Using Structural Equation Modeling
• • Composite Variables
  • Measurement
  • Measurement Scales
  • Coding
  • Data Distributions
• Principles of Structural Equation Modeling
• • Path Models With Latent Variables
  • Testing Theoretical Relationships
  • • Measurement Theory
    • Structural Theory
• PLS-SEM, CB-SEM, and Regressions Based on Sum Scores
• Considerations When Applying PLS-SEM
• • Key Characteristics of the PLS-SEM Method
  • Data Characteristics
  • • Minimum Sample Size Requirement
    • Missing Value Treatment
    • Nonnormal Data
    • Scales of Measurement
    • Secondary Data
  • Model Characteristics
• Guidelines for Choosing Between PLS-SEM and CB-SEM
• Organization of Remaining Chapters
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 2 • Specifying the Path Model and Examining Data

• Chapter Preview
• Stage 1: Specifying the Structural Model
• • Mediation
  • Moderation
  • Control Variables
• Stage 2: Specifying the Measurement Models
• • Reflective and Formative Measurement Models
  • Single-Item Measures and Sum Scores
  • Higher-Order Constructs
• 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

Chapter 3 • Path Model Estimation

• 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

Chapter 4 • Assessing PLS-SEM Results—Part I: Evaluation of the Reflective Measurement Models

• Chapter Preview
• Overview of Stage 5: Evaluation of Measurement Models
• Stage 5a: Assessing Results of Reflective Measurement Models
• • Step 1: Indicator Reliability
  • Step 2: Internal Consistency Reliability
  • Step 3: Convergent Validity
  • Step 4: Discriminant Validity
• Case Study Illustration—Evaluation of the Reflective Measurement Models (Stage 5a)
• • Running the PLS-SEM Algorithm
  • Reflective Measurement Model Evaluation
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 5 • Assessing PLS-SEM Results—Part II: Evaluation of the Formative Measurement Models

• 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
    • Bootstrap Confidence Intervals
• Case Study Illustration—Evaluation of the Formative Measurement Models (Stage 5b)
• • Extending the Simple Path Model
  • Reflective Measurement Model Evaluation (Recap)
  • Formative Measurement Model Evaluation
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 6 • Assessing PLS-SEM Results—Part III: Evaluation of the Structural Model

• Chapter Preview
• Stage 6: Structural Model Results Evaluation
• • Step 1: Assess the Structural Model for Collinearity
  • Step 2: Assess the Significance and Relevance of the Structural
  • Model Relationships
  • Step 3: Assess the Model’s Explanatory Power
  • Step 4: Assess the Model’s Predictive Power
  • • Number of Folds
    • Number of Repetitions
    • Prediction Statistic
    • Results Interpretation
    • Treating Predictive Power Issues
  • Step 5: Model Comparisons
• Case Study Illustration—Evaluation of the Structural Model (Stage 6)
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 7 • Mediator and Moderator Analysis

• Chapter Preview
• Mediation
• • Introduction
  • Measurement and Structural Model Evaluation in Mediation Analysis
  • Types of Mediating Effects
  • Testing Mediating Effects
  • Multiple Mediation
  • Case Study Illustration—Mediation
• Moderation
• • Introduction
  • Types of Moderator Variables
  • Modeling Moderating Effects
  • Creating the Interaction Term
  • • Product Indicator Approach
    • Orthogonalizing Approach
    • Two-Stage Approach
    • Guidelines for Creating the Interaction Term
  • Model Evaluation
  • Results Interpretation
  • Moderated Mediation and Mediated Moderation
  • Case Study Illustration—Moderation
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 8 • Outlook on Advanced Methods

• Chapter Preview
• Importance-Performance Map Analysis
• Necessary Condition Analysis
• Higher-Order Constructs
• Confirmatory Tetrad Analysis
• Examining Endogeneity
• Treating Observed and Unobserved Heterogeneity
• • Multigroup Analysis
  • Uncovering Unobserved Heterogeneity
• Measurement Model Invariance
• Consistent PLS-SEM
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Glossary
References
Index