Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach

Methodology in the Social Sciences

by Andrew F. Hayes

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. Data for all the examples are available on the companion website (www.afhayes.com), along with links to download PROCESS.
 
New to This Edition
*Chapters on using each type of analysis with multicategorical antecedent variables.
*Example analyses using PROCESS v3, with annotated outputs throughout the book.
*More tips and advice, including new or revised discussions of formally testing moderation of a mechanism using the index of moderated mediation; effect size in mediation analysis; comparing conditional effects in models with more than one moderator; using R code for visualizing interactions; distinguishing between testing interaction and probing it; and more.
*Rewritten Appendix A, which provides the only documentation of PROCESS v3, including 13 new preprogrammed models that combine moderation with serial mediation or parallel and serial mediation.
*Appendix B, describing how to create customized models in PROCESS v3 or edit preprogrammed models. 

Genres: Textbooks, Research

692 pages, Hardcover

First published January 1, 2013

About the author

Andrew F. Hayes, PhD, is Professor of Quantitative Psychology and Professor of Communication at The Ohio State University. He is the author of Statistical Methods for Communication Science and coeditor of the Sage Sourcebook on Advanced Data Analysis Methods for Communication Research, and has published many journal articles and book chapters in the areas of research methods, data analysis, public opinion, political communication, social psychology, and numerous other topics. Dr. Hayes is one of the founding editors of Communication Methods and Measures, for which he serves as Editor-in Chief through 2015. He teaches research design and data analysis at the undergraduate and graduate levels and frequently conducts workshops on moderation and mediation analysis throughout the world.

Reviews

[Dana]

Finally, an official book on this topic with all the info. in one place!

This will be so much better than hunting around on Preacher & Hayes' website and through their numerous publications to find instructions for that one, specific analysis we need.

[Daniel Christensen · Rating 5 out of 5]

Ok, so the only reason I bought the book is because I installed the PROCESS macro, and when you go to the hep doc it just tells you to buy the book. This seemed a bit mean to me.
That said, book is well written, with some nice insights into how the author thinks about statistics, and it's a good introduction to mediation-moderation.

[Courtney Koletar · Rating 5 out of 5]

This book is impeccably written. It's the most accessible stats textbook I've ever read.

[Becca Johnson · Rating 5 out of 5]

Super helpful for people who want to understand stats a bit better!

[Tara · Rating 5 out of 5]

Definitely adding this to my ‘must have’ list of textbooks. It will come in handy for dissertation and beyond.

[Dianne · Rating 5 out of 5]

This is the first advanced stats book I've read cover-to-cover and have understood! Dare I say that I actually enjoyed it? The new statistics are gaining momentum and are here to stay. This book is a miracle in its clarity. It is a rare find and should be on every researcher's bookshelf.