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Multiple Regression and Causal Analysis

McKee J. McClendon

Usually, multiple regression and causal analysis are treated as separate topics in separate books. McClendon has integrated the two areas within one text, oriented to their application in the social and behavioral sciences. After presenting an overview of issues and techniques for conducting causal analysis, the author devotes six chapters to regression analysis, but from the perspective of causal analysis. The final two chapters unite the two statistical methods, demonstrating their application in nonexperimental research. McClendon’s style emphasizes verbal explanation and assumes little background in mathematics or experimental design. Rather than bogging the reader down with mathematical derivations and computational formulations (now obsolete with the prevalence of computers), the text provides a thorough working knowledge of applied analysis. Social science students will find the book more readable and accessible than other texts in the field.

$59.95 list, 358 pages

10-digit ISBN: 1-57766-243-1

13-digit ISBN: 978-1-57766-243-3

© 1994

“This is a good, thorough text on multiple regression that is easy to understand and is especially nonthreatening to those with a limited math background.”  — Alfred DeMaris, Bowling Green State University 

“Excellent use of visuals to express concepts; covers a substantial range of topics in an efficient and eminently clear package.”  — Donald Lloyd, Florida State University

“Clear and concise presentation of multiple regression.”  — David Wright, Wichita State University

“I couldn’t find a better textbook than the one written by Dr. McClendon. It is well organized and written with excellent content and chart/figure illustrations. I’m sure professors and students will benefit greatly by using this book.”   — Jianjun Ji, University of Wisconsin, Eau Claire

“This is an excellent book for advanced regression courses. It is strong on modeling and easy to understand.”   — Robert Silverman, Wayne State University

“It is highly accessible by all students but challenging enough that the more advanced students are still stimulated.”  — Brian Stults, Florida State University

Table of Contents

1. Causality and Social Science

2. Bivariate Regression and Correlation

3. Multiple Regression

4. Tests of Statistical Significance

5. Nominal Independent Variables

6. Nonlinear Relationships

7. Nonadditive Relationships

8. Causal Analysis I

9. Causal Analysis II

Appendix. Statistical Tables