Regression Analysis and Linear Models: Concepts, Applications, and Implementation

by Andrew F. Hayes, Richard B. Darlington

Popular for its engaging writing and diverse, worked-through examples; helpful tips and cautions; and emphasis on conceptual understanding over mathematics, this introduction to linear regression analysis has been updated and reorganized for greater accessibility. Andrew F. Hayes and Richard B. Darlington introduce regression through the concept of statistical control of covariates. They explicate model construction and estimation, quantification and measurement of multivariate and partial association, group comparisons, use of multicategorical variables, mediation and path analysis, regression diagnostics, and many other important topics. Now with R code available throughout the book, along with SPSS, SAS, and Stata, the second edition includes separate chapters on model estimation/partial regression coefficients and partial association, including unpacking the important difference between semipartial and partial correlation. The companion website (www.afhayes.com) provides data files and code for the book's examples, along with online-only appendices on Hayes's PROCESS macro for regression analysis and on using regression as a prediction system.New to This EditionNew material on estimating, probing, and visualizing interactions in a regression model; simplifying a mediation analysis, especially for the construction of confidence intervals for inference about indirect effects; conducting a qualitative dominance analysis; and more.Incorporates use of the PROCESS macro for regression analysis, which makes it easier for users of different software to learn and share syntax across computing platforms.R code is now available throughout the book, along with SPSS, SAS and Stata.
 

600 pages, Hardcover

Expected publication April 1, 2027

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.