![]() Hayes illustrates each step in an analysis using diverse examples from published studies, and displays SPSS, SAS, and R code for each example. Using the principles of ordinary least squares regression, Andrew F. Constructing and Customizing Models in PROCESSĪcclaimed for its thorough presentation of mediation, moderation, and conditional process analysis, this book has been updated to reflect the latest developments in PROCESS for SPSS, SAS, and, new to this edition, R. Dichotomous, Ordinal, Count, and Survival OutcomesĪppendix B. Interaction between X and M in Mediation Analysisġ4.9. Can a Variable Simultaneously Mediate and Moderate Another Variable's Effect?ġ4.7. ![]() Should I Use Structural Equation Modeling Instead of Regression Analysis?ġ4.6. A Strategy for Approaching a Conditional Process Analysisġ4.3. Miscellaneous Topics and Some Frequently Asked Questionsġ4.1. Testing and Probing Moderation of Mediationġ3.5. Relative Conditional Indirect Effectsġ3.4. Looking at the Components of the Indirect Effect of Xġ3.3. Revisiting Sexual Discrimination in the Workplaceġ3.2. Conditional Process Analysis with a Multicategorical Antecedentġ3.1. Moderation of the Direct and Indirect Effects in a Conditional Process Modelġ3. Revisiting the Disaster Framing Studyġ2.2. Further Examples of Conditional Process Analysisġ2.1. Quantifying and Visualizing (Conditional) Indirect and Direct Effectsġ2. Estimation of a Conditional Process Model Using PROCESSġ1.5. Example: Hiding Your Feelings from Your Work Teamġ1.4. Conditional Direct and Indirect Effectsġ1.3. Examples of Conditional Process Models in the Literatureġ1.2. Fundamentals of Conditional Process Analysisġ1.1. When the Moderator Is Multicategoricalġ1. An Example from the Sex Discrimination in the Workplace Studyġ0.5. Moderation of the Effect of a Multicategorical Antecedent Variableġ0.2. Multicategorical Focal Antecedents and Moderatorsġ0.1. A Caution on Manual Centering and Standardizationġ0. The Estimation and Interpretation of Standardized Regression Coefficients in a Moderation Analysisĩ.3. Truths and Myths about Mean-Centeringĩ.2. Some Myths and Additional Extensions of Moderation Analysisĩ.1. The Equivalence between Moderated Regression Analysis and a 2 x 2 Factorial Analysis of Varianceĩ. Hierarchical versus Simultaneous EntryĨ.4. Interaction between Two Quantitative VariablesĨ.3. Moderation with a Dichotomous ModeratorĨ.2. Extending the Fundamental Principles of Moderation AnalysisĨ.1. Artificial Categorization and Subgroups AnalysisĨ. The Difference between Testing for Moderation and Probing Itħ.6. An Example: Climate Change Disasters and Humanitarianismħ.5. Conditional and Unconditional Effectsħ.2. Using a Different Group Coding Systemħ.1. An Example: Sex Discrimination in the WorkplaceĦ.3. Relative Total, Direct, and Indirect EffectsĦ.2. Mediation Analysis with a Multicategorical AntecedentĦ.1. Complementarity and Competition among MediatorsĦ. Models with Parallel and Serial Mediation Propertiesĥ.6. Example Using the Presumed Media Influence Studyĥ.5. Multiple Xs or Ys: Analyze Separately or Simultaneously?ĥ.1. Causal Steps, Scaling, Confounding, and Causal OrderĤ.4. An Example with Continuous X: Economic Stress among Small-Business OwnersĤ. Example with Dichotomous X: The Influence of Presumed Media Influenceģ.5. Estimation of the Direct, Indirect, and Total Effects of Xģ.3. Assumptions for Interpretation and Statistical Inferenceģ.2. Multicategorical Antecedent VariablesĢ.8. Alternative Explanations for AssociationĢ.7. Fundamentals of Linear Regression AnalysisĢ.3. Statistical and Conceptual Diagrams, and Antecedent and Consequent VariablesĢ. Correlation, Causality, and Statistical Modelingġ.5. Questions of Whether, If, How, and Whenġ.4.
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