This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying CD with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT. Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
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"...anyone with an interest in or need to carry out MR will find it invaluable."
―British Journal of Mathematical and Statistical Psychology
"I can't see how a practicing research psychologist could be without a copy."
―Dr. Steven P. Reise
University of California at Los Angeles
"Overall we think the book successfully reflects more contemporary issues, thinking, and advances in multiple regression and correlation....The general style and format, consistent with the previous editions, is understandable while still retaining depth and comprehensiveness."
―Drs. Lynda A. and Daniel W. King
Boston University School of Medicine
"I think VERY highly of this revision....The chapter on regression diagnostics and graphics (Ch. 4) is a wonderful addition. Also, the emphasis on confidence intervals is great, as is the extensive discussion on logistic regression."
―Dr. William F. Chaplin
University of Alabama, Tuscaloosa
"I have always felt that the book's major strength was its ability to blend careful, thoughtful explanation with a relatively non-technical exposition....I am happy to say that in my opinion this edition retains and furthermore expands upon this strength."
―Dr. Harry Reis
University of Rochester
This revised and updated edition is informed throughout by the application of Multiple Regression/Correlation (MRC) to the study of causality. MRC is seen here as a scientific rather than a technological tool - for understanding rather than blind "prediction". The presentation is non-mathematical and should be easy to grasp, with emphasis on concrete examples that are worked out in detail. The stress is on applications - not only to demonstrate the principles, but also to provide working models and show what kinds of applications are possible.
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