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Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Methodology in the Social Sciences) (Englisch) Gebundene Ausgabe – 14. Juni 2013

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  • Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Methodology in the Social Sciences)
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Produktbeschreibungen

Pressestimmen

"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, Department of Educational Psychology, University of Nebraska-Lincoln
"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, Department of Psychology, University of South Carolina
"This decidedly readable, informative book is perfectly suited for a range of audiences, from the novice graduate student not quite ready for SEM to the advanced statistics instructor. Even the seasoned quantitative methodologist will benefit from Hayes's years of accumulated wisdom as he expertly navigates this burgeoning--and at times inconsistent--literature. This book is particularly well suited for graduate-level courses. Hayes brings conditional process analysis to life with such passion that even the most 'stat-o-phobic' will become convinced that they too can master SPSS (or SAS) process. The thoughtful use of real-life examples, accompanied by SPSS and SAS syntax and output, makes the book highly accessible."--Shelley Brown, PhD, Department of Psychology, Carleton University, Canada

Über den Autor und weitere Mitwirkende

Andrew F. Hayes, PhD, is Professor of Quantitative Psychology at The Ohio State University. His research and writing on data analysis has been published widely, and he is the author of Introduction to Mediation, Moderation, and Conditional Process Analysis and Statistical Methods for Communication Science, as well as coauthor, with Richard B. Darlington, of Regression Analysis and Linear Models. Dr. Hayes teaches data analysis, primarily at the graduate level, and frequently conducts workshops on statistical analysis throughout the world. His website is www.afhayes.com.


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Format: Gebundene Ausgabe
In the past 10 years or so, Andrew Hayes has established himself as one of the leading researchers in the statistical analysis of mediation and moderation. What makes his work unique is his understanding of the everyday problems that non-methodologists are confronted with in their work. His PROCESS macro, which has facilitated and improved the analysis of mediation and moderated mediation patterns, clearly attests to the service-oriented character of his work.

In "Introduction to Mediation, Moderation, and Conditional Process Analysis," Hayes continues with his service-oriented work for social scientists who are interested in patterns of how variables are related to, or influence, each other. The book covers much of the issues that Hayes has dealt with in the past decade, notably his work on mediation, the proper investigation of moderation, and the combination of the two, moderated mediation, that is. Similar to Hayes' previous work, the book is largely written in a non-technical manner. His target audience are researchers who aim at rigorous analysis of their data, but may not have the ability or time to work through the more technical statistical literature. Hayes does not assume too much statistical knowledge from his readers, which makes the book easily accessible. Actually, in chapters 1 to 3, Hayes explains the basics of correlation and causality, as well as simple and multiple linear regression. Still, the book is not suitable for statistical novices in my view. A previous rough understanding of multiple regression analysis and a basic grasp of traditional (stepwise, "Baron and Kenny" type) approaches to mediation are helpful to take full advantage of the book.

The book is divided in four parts.
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Format: Gebundene Ausgabe Verifizierter Kauf
This book is a must-have for all researchers interested in moderation, mediation and conditional process analyses! Hayes’ book is a great resource for everybody who wants to understand and competently conduct moderation, mediation and conditional process analyses. Statistics are explained in easy-to-understand language and provide an informative background for the use of the PROCESS macro (developed by Hayes). Application scenarios for basic and more complex statistical models are described with relevant detail and references provided to exemplary papers. In particular, I appreciate the ‘miscellaneous topics’: They answer all questions with regard to effects sizes, mean centering, standardization, etc. For those still using the Baron & Kenny’s ‘causal steps-approach’, chapter 6.1 is an essential read. In a second edition, it would be helpful to have references to the specific models in the table of contents.
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This book helped me tremendously in conducting more advanced SPSS analyses , in understanding the why behind it and last but not least in writing about my findings.
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 4.7 von 5 Sternen 30 Rezensionen
5 von 5 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen This book will change your life. 24. April 2014
Von Mountain Man - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Well it can't get your kid to eat broccoli or your dog to stop pooping in the house, but if you do quantitative work and are concerned about causality, it will at least change your research.

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.
13 von 14 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Good stuff but missing a good output explanation 31. Juli 2013
Von BizDoc - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
I had been looking forward to this book for some time because I was interested in learning how to conduct these kinds of analyses but I found it hard to teach myself the process by reading the existing articles. It does a nice job of explaining the basics of the analyses and Process is a great macro for SPSS. However, I was also really hoping that the book would contain a detailed breakdown of what information is contained on the output and how to interpret it. Unfortunately, it doesn't have that. It has sample output but it doesn't really go through and explain everything that's contained in the output. It seems to just assume that you know how to read the output which is a little odd for a book that's meant to be an introduction.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Great book - a must have reference book for mediation analysis 27. November 2013
Von E. Minton - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Great book. I have only two stats books that I frequently refer to. One of Hayes' book for mediation (and conditional process analysis) and the second is Andy Field's guide to SPSS. These two together tell you everything you need to know about basic stats in SPSS. Hayes' book is clear, uses great examples, and explains concepts well for those that know the basics of stats (but is not overwhelming with formulas). A must for anyone doing mediation analysis.
4 von 4 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Very clear and relevant text on mediation and moderation 6. November 2013
Von H. Bergsieker - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Excellent, accessible explanation of how to optimally test relationships between variables in regression. I teach Ph.D.-level statistics courses and am considering assigning this text in the future. Hayes has done a true service to science by writing this book and the associated macro tools.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen All one needs to know about Mediation and Moderation 7. Juli 2016
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
I feel like I have a firm grasp of mediation and moderation after reading this book!
Waren diese Rezensionen hilfreich? Wir wollen von Ihnen hören.