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Introduction to Mediation, Moderation, and Conditional Process Analysis This engaging book explains the fundamentals of mediation and moderation analysis and their integration 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 Full description

Quantitative methods in social research --- Social sciences --- Mediation --- Regression analysis. --- Sciences sociales --- Médiation --- Analyse de régression --- Statistical methods. --- Méthodes statistiques --- Regression Analysis --- Analyse de regression --- Statistical methods --- Methodes statistiques --- Mediation (Statistics) --- #SBIB:303H520 --- -Mediation --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Good offices (Mediation) --- Conflict management --- Dispute resolution (Law) --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Law and legislation --- Mediation (Statistics). --- Médiation --- Analyse de régression --- Méthodes statistiques --- Mediation analysis (Statistics) --- Mediational analysis (Statistics) --- Statistical mediation --- Statistical mediation analysis --- Analyse de régression. --- Méthodes statistiques. --- Social sciences - Statistical methods --- Sciences sociales - Methodes statistiques

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Lauded for its easy-to-understand, conversational discussion of the fundamentals of mediation, moderation, and conditional process analysis, this book has been fully revised with 50% new content, including sections on working with multicategorical antecedent variables, the use of PROCESS version 3 for SPSS and SAS for model estimation, and annotated PROCESS v3 outputs. Using the principles of ordinary least squares regression, Andrew F. Hayes carefully explains procedures for testing hypotheses about the conditions under and the mechanisms by which causal effects operate, as well as the moderation of such mechanisms. Hayes shows how to estimate and interpret direct, indirect, and conditional effects; probe and visualize interactions; test questions about moderated mediation; and report different types of analyses.

Social sciences --- Mediation (Statistics) --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Mediation analysis (Statistics) --- Mediational analysis (Statistics) --- Statistical mediation --- Statistical mediation analysis --- Statistical methods --- Mediation (Statistics). --- Regression analysis. --- Statistical methods. --- #SBIB:303H520 --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Quantitative methods in social research --- Quantitative methods (economics) --- Multivariate analysis --- Structural equation modeling --- Regression Analysis --- Sciences sociales --- Analyse de régression. --- Méthodes statistiques --- Social sciences - Statistical methods --- Analyse de régression. --- Méthodes statistiques

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Acclaimed 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. Using the principles of ordinary least squares regression, Andrew F. Hayes illustrates each step in an analysis using diverse examples from published studies, and displays SPSS, SAS, and R code for each example. Procedures are outlined for estimating and interpreting direct, indirect, and conditional effects; probing and visualizing interactions; testing hypotheses about the moderation of mechanisms; and reporting different types of analyses. Readers gain an understanding of the link between statistics and causality, as well as what the data are telling them. The companion website (www.afhayes.com) provides data for all the examples, plus the free PROCESS download. New to This Edition *Rewritten Appendix A, which provides the only documentation of PROCESS, including a discussion of the syntax structure of PROCESS for R compared to SPSS and SAS. *Expanded discussion of effect scaling and the difference between unstandardized, completely standardized, and partially standardized effects. *Discussion of the meaning of and how to generate the correlation between mediator residuals in a multiple-mediator model, using a new PROCESS option. *Discussion of a method for comparing the strength of two specific indirect effects that are different in sign. *Introduction of a bootstrap-based Johnson-Neyman-like approach for probing moderation of mediation in a conditional process model. *Discussion of testing for interaction between a causal antecedent variable [ital]X[/ital] and a mediator [ital]M[/ital] in a mediation analysis, and how to test this assumption in a new PROCESS feature.

Quantitative methods in social research --- Quantitative methods (economics) --- Social sciences --- Mediation (Statistics) --- Regression analysis --- Sciences sociales --- Analyse de régression. --- Statistical methods --- Méthodes statistiques --- Mediation (Statistics). --- Regression analysis. --- Statistical methods. --- Analyse de régression. --- Méthodes statistiques

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Quantitative methods in social research