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Full Description
Explaining the fundamentals of mediation and moderation analysis, this engaging book also shows how to integrate the two using an innovative strategy known as conditional process analysis. Procedures are described for testing hypotheses about the mechanisms by which causal effects operate, the conditions under which they occur, and the moderation of mechanisms. Relying on the principles of ordinary least squares regression, Andrew Hayes carefully explains the estimation and interpretation of direct and indirect effects, probing and visualization of interactions, and testing of questions about moderated mediation. Examples using data from published studies illustrate how to conduct and report the analyses described in the book. Of special value, the book introduces and documents PROCESS, a macro for SPSS and SAS that does all the computations described in the book. The companion website (www.afhayes.com) offers free downloads of PROCESS plus data files for the book's examples.Unique features include:*Compelling examples (presumed media influence, sex discrimination in the workplace, and more) with real data; boxes with SAS, SPSS, and PROCESS code; and loads of tips, including how to report mediation, moderation and conditional process analyses.*Appendix that presents documentation on use and features of PROCESS. *Online supplement providing data, code, and syntax for the book's examples.
Contents
I. FUNDAMENTAL CONCEPTS1. Introduction1.1. A Scientist in Training1.2. Questions of Whether, If, How, and When1.3. Conditional Process Analysis1.4. Correlation, Causality, and Statistical Modeling1.5. Statistical Software1.6. Overview of this Book1.7. Chapter Summary2. Simple Linear Regression 2.1. Correlation and Prediction2.2. The Simple Linear Regression Equation2.3. Statistical Inference2.4. Assumptions for Interpretation and Statistical Inference2.5. Chapter Summary3. Multiple Linear Regression 3.1. The Multiple Linear Regression Equation3.2. Partial Association and Statistical Control3.3. Statistical Inference in Multiple Regression3.4. Statistical and Conceptual Diagrams3.5. Chapter SummaryII. MEDIATION ANALYSIS4. The Simple Mediation Model 4.1. The Simple Mediation Model4.2. Estimation of the Direct, Indirect, and Total Effects of X4.3. Example with Dichotomous X: The Influence of Presumed Media Influence4.4. Statistical Inference4.5. An Example with Continuous X: Economic Stress among Small Business Owners4.6. Chapter Summary5. Multiple Mediator Models5.1. The Parallel Multiple Mediator Model5.2. Example Using the Presumed Media Influence Study5.3. Statistical Inference5.4. The Serial Multiple Mediator Model5.5. Complementarity and Competition among Mediators5.6. OLS Regression versus Structural Equation Modeling5.7. Chapter SummaryIII. MODERATION ANALYSIS6. Miscellaneous Topics in Mediation Analysis 6.1. What About Baron and Kenny?6.2. Confounding and Causal Order6.3. Effect Size6.4. Multiple Xs or Ys: Analyze Separately or Simultaneously?6.5. Reporting a Mediation Analysis6.6. Chapter Summary7. Fundamentals of Moderation Analysis 7.1. Conditional and Unconditional Effects7.2. An Example: Sex Discrimination in the Workplace7.3. Visualizing Moderation7.4. Probing an Interaction7.5. Chapter Summary8. Extending Moderation Analysis Principles 8.1. Moderation Involving a Dichotomous Moderator8.2. Interaction between Two Quantitative Variables8.3. Hierarchical versus Simultaneous Variable Entry8.4. The Equivalence between Moderated Regression Analysis and a 2 x 2 Factorial Analysis of Variance8.5. Chapter Summary9. Miscellaneous Topics in Moderation Analysis 9.1. Truths and Myths about Mean Centering9.2. The Estimation and Interpretation of Standardized Regression Coefficients in a Moderation Analysis9.3. Artificial Categorization and Subgroups Analysis9.4. More Than One Moderator9.5. Reporting a Moderation Analysis9.6. Chapter SummaryIV. CONDITIONAL PROCESS ANALYSIS10. Conditional Process Analysis 10.1. Examples of Conditional Process Models in the Literature10.2. Conditional Direct and Indirect Effects10.3. Example: Hiding Your Feelings from Your Work Team10.4. Statistical Inference10.5. Conditional Process Analysis in PROCESS10.6. Chapter Summary11. Further Examples of Conditional Process Analysis 11.1. Revisiting the Sexual Discrimination Study11.2. Moderation of the Direct and Indirect Effects in a Conditional Process Model11.3. Visualizing the Direct and Indirect Effects11.4. Mediated Moderation11.5. Chapter Summary12. Miscellaneous Topics in Conditional Process Analysis 12.1. A Strategy for Approaching Your Analysis12.2. Can a Variable Simultaneously Mediate and Moderate Another Variable's Effect?12.3. Comparing Conditional Indirect Effects and a Formal Test of Moderated Mediation12.4. The Pitfalls of Subgroups Analysis12.5. Writing about Conditional Process Modeling12.6. Chapter SummaryAppendix A. Using PROCESS Appendix B. Monte Carlo Confidence Intervals in SPSS and SAS
