Multiple Regression in Behavioral Research

If you're serious about learning quantitative research, well, this man takes his work very, very seriously, much to our benefit. He has an extraordinary intellect. I would call the book "magisterial" if his self-importance weren't taken to such hilarious heights. But that comic relief is welcome, too. The book plumbs the depths of the general linear model, providing extensive, rigorous, extremely well-considered treatment of statistical control, linear regression, analysis of covariance, logistic regression, and structural equation modeling. Includes important sections on topics such as nonlinear relationships and interactions. Has sections that I reread every few months to a year because the ideas are so important to my understanding of analytic issues and so hard to come by anywhere else. It's not for beginners, but don't wait too long! You'll kick yourself for all the insights you could have developed, and all the conceptual and technical mistakes you could have avoided. Two drawbacks. There is too much attention to SPSS, SAS, and other code for many people's taste. Also, it is weighted down by unnecessarily precise calculation, overemphasizing hypothesis testing and statistical significance at the expense of the size of effects. One of the more insidious statistical mistakes.

very pleased with the prompt delivery and ease of placing my order - will certainly order my books this way in the future!

The author explains multiple regression in a way that is easy to follow. I am actually a beginner in statistics and had experiences in reading some other books which looked to me as if they were written by aliens. I would recommend this book for courses offered to graduate students.

This is a wonderful text for a class primarily dedicated to multiple regression. I own and have read many regression textbooks, and this continues to be one of the very best! The reader reviews below appear to mostly be expressing frustration with instructors, and not this text. If you are taking an introductory course in which regression is one of many topics, this book may be too advanced for your needs (and may be a poor choice by your instructor!). However, if you are taking a course dedicated to regression (linear and logistic; or general linear models in general), this is one of the very best text available!

Pedhazur's third edition of this text that he began with Kerlinger is an excellent introduction to linear regression. I use this text in a statistics course that I teach to first-year graduate students and they have responded favourably to me about the book. Pedhazur is a stickler for 'getting it right,' which is critically important for the serious student to learn at this stage. The book is replete with examples of both doing it right and doing it wrong (the latter culled from the literature). If you want to learn how to do linear regression correctly, this text is excellent within its scope as a primer. The introductory chapters on multilevel modelling and logistic regression are nice touches. All in all a very useful text.