- Hardcover: 507 pages
- Publisher: Guilford Press; 1 edition (14 Jun. 2013)
- Language: English
- ISBN-10: 1609182308
- ISBN-13: 978-1609182304
- Product Dimensions: 3.2 x 18.4 x 26 cm
- Average Customer Review: 4.7 out of 5 stars See all reviews (3 customer reviews)
- Amazon Bestsellers Rank: 251,767 in Books (See Top 100 in Books)
- See Complete Table of Contents
Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Methodology in the Social Sciences) Hardcover – 14 Jun 2013
|New from||Used from|
- Choose from over 13,000 locations across the UK
- Prime members get unlimited deliveries at no additional cost
- Find your preferred location and add it to your address book
- Dispatch to this address when you check out
Frequently Bought Together
Customers Who Bought This Item Also Bought
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your e-mail address or mobile phone number.
More About the Author
"Mediation and moderation are two of the most widely used statistical tools in the social sciences. Students and experienced researchers have been waiting for a clear, engaging, and comprehensive book on these topics for years, but the wait has been worth it--this book is an absolute winner. With his usual clarity, Hayes has written what will become the default resource on mediation and moderation for many years to come." - Andy Field, PhD, School of Psychology, University of Sussex, United Kingdom
"Hayes provides an accessible, thorough introduction to the analysis of models containing mediators, moderators, or both. The text is easy to follow and written at a level appropriate for an introductory graduate course on mediation and moderation analysis. The book is also an extremely useful resource for applied researchers interested in analyzing conditional process models. One strength is the inclusion of numerous examples using real data, with step-by-step instructions for analysis of the data and interpretation of the results. This book's largest contribution to the field is its replacement of the confusing terminology of mediated moderation and moderated mediation with the clearer and broader term conditional process model." - Matthew Fritz, PhD, Virginia Polytechnic Institute and State University, USA
"A welcome contribution. This book's accessible language and diverse set of examples will appeal to a wide variety of substantive researchers looking to explore how or why, and under what conditions, relationships among variables exist. Hayes has a unique ability to effectively communicate technical material to nontechnical audiences. He facilitates application of several cutting-edge statistical models by providing practical, well-oiled machinery for conducting the analyses in practice. I can use this book to enhance my graduate-level mediation class by extending the course to include more coverage on differentiating mediation versus moderation and on conditional process models that simultaneously evaluate both effects together." - Amanda Jane Fairchild, PhD, University of South Carolina, USA
About the Author
Andrew F. Hayes, PhD, is Professor of Quantitative Psychology 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. His website is www.afhayes.com.
Inside This Book(Learn More)
What Other Items Do Customers Buy After Viewing This Item?
Top Customer Reviews
Most Helpful Customer Reviews on Amazon.com (beta)
This book is incredible. Incredibly well written and clear explanations. If you have a decent idea about how regressions work, you can probably skip the first few chapters, but I wouldn't recommend it. I thought I had a clear understanding of regression analysis, but the way Hayes explained it gave me a new appreciation for some of the subtleties. And that's not even the main text!
I have fundamentally shifted the way I think about data with an understanding of how these tools work. I was always a bit suspicious of the Baron & Kenny mediation; while it is useful, it has some flaws. Hayes explains the bootstrapping methodology in a manner that gave me insight into both what those flaws are, and why this methodology is more powerful and consistent.
The clear explanations are incredible, but the real piece that puts this over the top is the fact that Hayes provides the macros for free on his website. Instead of spending loads of time figuring out how to translate my statistical knowledge into code, I can implement these ideas immediately. I know some people prefer to have absolute control over these processes, but I am not one of them.
In short, you need this book.