2016, Hardcover
ISBN 9781462521135
7" x 10", 664 Pages, $85.00
DISCOUNT PRICE: $68.00
Regression Analysis and Linear Models
Concepts, Applications, and Implementation
Richard B. Darlington and Andrew F. Hayes
“This is a great textbook for students who have only basic knowledge of statistics yet would like to
gain a deep conceptual understanding of regression. The book is up to date in current methods in
regression, with strong examples using SAS/SPSS/STATA.”
—Chris Oshima, PhD, Department of Educational Policy Studies, Georgia State University
“A terrific addition to the regression literature. I am often asked, 'How do I determine which
regressor(s) is/are the most important?' The treatment of this topic is excellent, and the authors have
done a fantastic job of bringing important issues to light. The applied nature of the text and the
interweaving of software syntax and output are major improvements over similar books. I like the
fact that the book has software package information for SPSS, SAS, and STATA. It has a nice
balance; not too technical on the statistical side, but not simply a 'how to' on the software side. I
could see this book being used as the main text in our department's graduate-level regression
course.”
—Scott C. Roesch, PhD, Department of Psychology, San Diego State University
“This fantastic introduction to the general linear model takes the reader from first principles through
to widely used techniques such as mediation and path analysis. The clear writing makes it a
pleasure to read. Students will find the book an invaluable resource. There are plenty of insights,
too, for even seasoned researchers and data analysts. Instructors and students will appreciate the
logical structure and bite-sized chapters that break the material up into manageable chunks.”
—Andy Field, PhD, Professor of Child Psychopathology, University of Sussex, United Kingdom
“If you want to get the most bang for your buck out of your statistical training, investing in learning
regression and linear models is the way to go. Nonetheless, many people find linear modeling to be
confusing at first. This book breaks down all walls to mastering this fundamental analysis by
providing a complete guide in an approachable, conversational style. The book begins with a
comprehensive introduction to linear models and continues on to cover the most useful advanced
topics, such as logistic regression, mediation and path analysis, and multilevel models. A
'must-have' desk reference for entry-level learners and long-time practitioners alike.”
—Elizabeth Page-Gould, PhD, Canada Research Chair in Social Psychophysiology, University of
Toronto
Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear
regression analysis to students and researchers across the social, behavioral, consumer, and health
sciences. Coverage includes model construction and estimation, quantification and measurement of
multivariate and partial associations, statistical control, group comparisons, moderation analysis,
mediation and path analysis, and regression diagnostics, among other important topics. Engaging
worked-through examples demonstrate each technique, accompanied by helpful advice and cautions.
The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R.
The author's website (www.afhayes.com) provides datasets for the book's examples as well as the
RLM macro for SPSS and SAS.
Find full information about this title online: www.guilford.com/p/darlington
