Review
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"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
“This book elegantly presents both the basic and advanced issues
of mediation and moderation analysis…it will be beneficial for
graduate students and applied researchers who are interested in
causal mechanisms using linear models….[T]his is a very good
textbook for applied researchers in social sciences. It covers
mediation and moderation analysis using regression techniques
quite nicely. The online materials of this book provide the data
and software code for SAS and SPSS, which are very helpful
supplements. I think this book could be very useful for both
preliminary and advanced readers who are interested in mediation
and moderation analysis.”
(Journal of American Statistical Association 2014-11-13)
“The book is very readable and conversational, providing many
interesting and useful examples….I found this to be a very nice
book that is readable enough for the intermediate statistics user
but with enough technical detail to appeal to advanced users as
well. The first three sections provide a thorough presentation of
regression analysis and its use in answering questions of
mediation and moderation. The inclusion of helpful SPSS macros
and SAS programs for better estimation of these models is a very
attractive quality….The final section on conditional process
analysis is illuminating and thought-provoking, and for the
reader unfamiliar with these topics will definitely peak
interest. This book would make an excellent textbook for an
advanced graduate-level multiple regression course, or just a
great resource for the interested reader.” (Journal of
Educational Measurement 2014-10-01)
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About the Author
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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. Dr. Hayes 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. He 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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