Introduction to Mediation, Moderation, and Conditional Process Analysis

Second Edition
A Regression-Based Approach

Andrew F. Hayes

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December 13, 2017
ISBN 9781462534654
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692 Pages
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I. Fundamentals

1. Introduction

1.1. A Scientist in Training

1.2. Questions of Whether, If, How, and When

1.3. Conditional Process Analysis

1.4. Correlation, Causality, and Statistical Modeling

1.5. Statistical and Conceptual Diagrams, and Antecedent and Consequent Variables

1.6. Statistical Software

1.7. Overview of This Book

1.8. Chapter Summary

2. Fundamentals of Linear Regression Analysis

2.1. Correlation and Prediction

2.2. The Simple Linear Regression Model

2.3. Alternative Explanations for Association

2.4. Multiple Linear Regression

2.5. Measures of Model Fit

2.6. Statistical Inference

2.7. Multicategorical Antecedent Variables

2.8. Assumptions for Interpretation and Statistical Inference

2.9. Chapter Summary

II. Mediation Analysis

3. The Simple Mediation Model

3.1. The Simple Mediation Model

3.2. Estimation of the Direct, Indirect, and Total Effects of X

3.3. Example with Dichotomous X: The Influence of Presumed Media Influence

3.4. Statistical Inference

3.5. An Example with Continuous X: Economic Stress among Small-Business Owners

3.6. Chapter Summary

4. Causal Steps, Confounding, and Causal Order

4.1. What about Baron and Kenny?

4.2. Confounding and Causal Order

4.3. Effect Size

4.4. Statistical Power

4.5. Multiple Xs or Ys: Analyze Separately or Simultaneously?

4.6. Chapter Summary

5. More Than One Mediator

5.1. The Parallel Multiple Mediator Model

5.2. Example Using the Presumed Media Influence Study

5.3. Statistical Inference

5.4. The Serial Multiple Mediator Model

5.5. Models With Parallel and Serial Mediation Properties

5.6. Complementarity and Competition among Mediators

5.7. Chapter Summary

6. Mediation Analysis with a Multicategorical Antecedent X

6.1. Relative Total, Direct, and Indirect Effects

6.2. An Example: Sex Discrimination in the Workplace

6.3. Using a Different Group Coding System

6.4. Some Miscellaneous Issues

6.5. Chapter Summary

III. Moderation Analysis

7. Fundamentals of Moderation Analysis

7.1. Conditional and Unconditional Effects

7.2. An Example: Climate Change Disasters and Humanitarianism

7.3. Visualizing Moderation

7.4. Probing an Interaction

7.5. The Difference between Testing for Moderation and Probing It

7.6. Artificial Categorization and Subgroups Analysis

7.7. Chapter Summary

8. Extending the Fundamentals of Moderation Analysis

8.1. Moderation with a Dichotomous Moderator

8.2. Interaction between Two Quantitative Variables

8.3. Hierarchical versus Simultaneous Entry

8.4. The Equivalence between Moderated Regression Analysis and a 2 × 2 Factorial Analysis of Variance

8.5. Chapter Summary

9. Some Myths and Further Extensions of Moderation Analysis

9.1. Truths and Myths about Mean Centering

9.2. The Estimation and Interpretation of Standardized Regression Coefficients in a Moderation Analysis

9.3. A Caution on Manual Centering and Standardization

9.4. More than One Moderator

9.5. Comparing Conditional Effects

9.6. Chapter Summary

10. Multicategorical Focal Antecedents and Moderators

10.1. Moderation of the Effect of a Multicategorical Antecedent Variable

10.2. An Example from the Sex Discrimination in the Work Place Study

10.3. Visualizing the Model

10.4. Probing the Interaction

10.5. When the Moderator is Multicategorical

10.6. Using a Different Coding System

10.7. Chapter Summary

IV. Conditional Process Analysis

11. Fundamentals of Conditional Process Analysis

11.1. Examples of Conditional Process Models in the Literature

11.2. Conditional Direct and Indirect Effects

11.3. Example: Hiding Your Feelings from Your Work Team

11.4. Estimation of a Conditional Process Model using PROCESS

11.5. Quantifying and Visualizing (Conditional) Indirect and Direct Effects

11.6. Statistical Inference

11.7. Chapter Summary

12. Further Examples of Conditional Process Analysis

12.1. Revisiting the Disaster Framing Study

12.2. Moderation of the Direct and Indirect Effects in a Conditional Process Model

12.3. Statistical Inference

12.4. Mediated Moderation

12.5. Chapter Summary

13. Conditional Process Analysis with a Multicategorical Antecedent

13.1. Revisiting Sexual Discrimination in the Work Place

13.2. Looking at the Components of the Indirect Effect of X

13.3. Relative Conditional Indirect Effects

13.4. Testing and Probing Moderation of Mediation

13.5. Relative Conditional Direct Effects

13.6. Putting It All Together

13.7. Chapter Summary

V. Miscellanea

14. Miscellaneous Topics and Some Frequently Asked Questions

14.1. A Strategy for Approaching a Conditional Process Analysis

14.2. How Do I Write about This?

14.3. Should I Use Structural Equation Modeling Instead of Regression Analysis?

14.4. The Pitfalls of Subgroups Analysis

14.5. Can a Variable Simultaneously Mediate and Moderate Another Variable’s Effect?

14.6. Interaction between X and M in Mediation Analysis

14.7. Repeated Measures Designs

14.8. Dichotomous, Ordinal, Count, and Survival Outcomes

14.9. Chapter Summary

Appendices

Appendix A. Using PROCESS

Appendix B. Constructing and Customizing Models in PROCESS

Appendix C. Monte Carlo Confidence Intervals in SPSS and SAS

References

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