Introduction to mediation, moderation, and conditional process analysis : a regression-based approach [texte imprimé] / Andrew F. Hayes, Auteur  . -  2nd . - The Guilford Press, 2018 . - xx, 692 p. : illustrations. - (Methodology in the social sciences) .
ISBN : 978-1-462-53465-4
Langues : Anglais (eng)

Catégories :	Statistiques
Mots-clés :	Social sciences  Statistical methods  Mediation (Statistics)  Regression analysis
Index. décimale :	001.4 Recherche et méthodes statistiques
Note de contenu :	I. Fundamentals1. 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 and Conceptual Diagrams, and Antecedent and Consequent Variables1.6. Statistical Software1.7. Overview of This Book1.8. Chapter Summary2. Fundamentals of Linear Regression Analysis2.1. Correlation and Prediction2.2. The Simple Linear Regression Model2.3. Alternative Explanations for Association2.4. Multiple Linear Regression2.5. Measures of Model Fit2.6. Statistical Inference2.7. Multicategorical Antecedent Variables2.8. Assumptions for Interpretation and Statistical Inference2.9. Chapter SummaryII. Mediation Analysis3. The Simple Mediation Model3.1. The Simple Mediation Model3.2. Estimation of the Direct, Indirect, and Total Effects of X3.3. Example with Dichotomous X: The Influence of Presumed Media Influence3.4. Statistical Inference3.5. An Example with Continuous X: Economic Stress among Small-Business Owners3.6. Chapter Summary4. Causal Steps, Confounding, and Causal Order4.1. What about Baron and Kenny?4.2. Confounding and Causal Order4.3. Effect Size4.4. Statistical Power4.5. Multiple Xs or Ys: Analyze Separately or Simultaneously?4.6. Chapter Summary5. More Than One Mediator5.1. The Parallel Multiple Mediator Model5.2. Example Using the Presumed Media Influence Study5.3. Statistical Inference5.4. The Serial Multiple Mediator Model5.5. Models With Parallel and Serial Mediation Properties5.6. Complementarity and Competition among Mediators5.7. Chapter Summary6. Mediation Analysis with a Multicategorical Antecedent X6.1. Relative Total, Direct, and Indirect Effects6.2. An Example: Sex Discrimination in the Workplace6.3. Using a Different Group Coding System6.4. Some Miscellaneous Issues6.5. Chapter SummaryIII. Moderation Analysis7. Fundamentals of Moderation Analysis7.1. Conditional and Unconditional Effects7.2. An Example: Climate Change Disasters and Humanitarianism7.3. Visualizing Moderation7.4. Probing an Interaction7.5. The Difference between Testing for Moderation and Probing It7.6. Artificial Categorization and Subgroups Analysis7.7. Chapter Summary8. Extending the Fundamentals of Moderation Analysis8.1. Moderation with a Dichotomous Moderator8.2. Interaction between Two Quantitative Variables8.3. Hierarchical versus Simultaneous Entry8.4. The Equivalence between Moderated Regression Analysis and a 2 x 2 Factorial Analysis of Variance8.5. Chapter Summary9. Some Myths and Further Extensions of Moderation Analysis9.1. Truths and Myths about Mean Centering9.2. The Estimation and Interpretation of Standardized Regression Coefficients in a Moderation Analysis9.3. A Caution on Manual Centering and Standardization9.4. More than One Moderator9.5. Comparing Conditional Effects9.6. Chapter Summary10. Multicategorical Focal Antecedents and Moderators10.1. Moderation of the Effect of a Multicategorical Antecedent Variable10.2. An Example from the Sex Discrimination in the Work Place Study10.3. Visualizing the Model10.4. Probing the Interaction10.5. When the Moderator is Multicategorical10.6. Using a Different Coding System10.7. Chapter SummaryIV. Conditional Process Analysis11. Fundamentals of Conditional Process Analysis11.1. Examples of Conditional Process Models in the Literature11.2. Conditional Direct and Indirect Effects11.3. Example: Hiding Your Feelings from Your Work Team11.4. Estimation of a Conditional Process Model using PROCESS11.5. Quantifying and Visualizing (Conditional) Indirect and Direct Effects11.6. Statistical Inference11.7. Chapter Summary12. Further Examples of Conditional Process Analysis12.1. Revisiting the Disaster Framing Study12.2. Moderation of the Direct and Indirect Effects in a Conditional Process Model12.3. Statistical Inference12.4. Mediated Moderation12.5. Chapter Summary13. Conditional Process Analysis with a Multicategorical Antecedent13.1. Revisiting Sexual Discrimination in the Work Place13.2. Looking at the Components of the Indirect Effect of X13.3. Relative Conditional Indirect Effects13.4. Testing and Probing Moderation of Mediation13.5. Relative Conditional Direct Effects13.6. Putting It All Together13.7. Chapter SummaryV. Miscellanea14. Miscellaneous Topics and Some Frequently Asked Questions14.1. A Strategy for Approaching a Conditional Process Analysis14.2. How Do I Write about This?14.3. Should I Use Structural Equation Modeling Instead of Regression Analysis?14.4. The Pitfalls of Subgroups Analysis14.5. Can a Variable Simultaneously Mediate and Moderate Another Variable's Effect?14.6. Interaction between X and M in Mediation Analysis14.7. Repeated Measures Designs14.8. Dichotomous, Ordinal, Count, and Survival Outcomes14.9. Chapter SummaryAppendicesAppendix A. Using PROCESSAppendix B. Constructing and Customizing Models in PROCESSAppendix C. Monte Carlo Confidence Intervals in SPSS and SASReferencesAbout the Autho