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Multiple Regression: Testing and Interpreting Interactions

By Leona S. AikenStephen G. West ( Sage Publications, Inc )

Release Date: 1991-01-01
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"I think that the coverage of the text is excellent. It carves out a seriously neglected area and it very thoroughly covers the topic. The authors are very knowledgeable concerning the literature. This is an excellent text that provides a detailed, yet comprehensible account of how to estimate, test, and probe interactions in regression models."

--David A. Kenny, University of Connecticut

"Leona S. Aiken and Stephen G. West do an excellent job of structuring, testing, and interpreting multiple regression models containing interactions, curvilinear effects, or a combination of both. Procedures for testing and graphical displays of interactions between categorical variables have been done for years but none seems to have provided a comprehensive treatment or guideline for the analysis of interactions between continuous variables. . . . Aiken and West, however, address those issues quite effectively and thoroughly. . . . An aid to any graduate and/or researcher in their analysis of continuous variables. Highly recommended for graduate libraries."

--Choice

"The book would serve very well as a reference for applied researchers and methodologists. . . . In particular, this would be an excellent reference for anyone who encounters a multivariable prediction problem and has reason to believe that either a nonlinear model or a model including a variable product term would be appropriate."

--Contemporary Psychology

Researchers in a variety of disciplines frequently encounter problems in which interactions are predicted between two or more continuous variables. However, the current literature regarding how to analyze, interpret, and present interactions in multiple regression has been confusing. In this comprehensive volume, Leona S. Aiken and Stephen G. West provide academicians and researchers with a clear set of prescriptions for estimating, testing, and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models or for those enrolled in courses on multivariate statistics.

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Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, Third Edition	Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences)	Using Multivariate Statistics (5th Edition)	Statistical Power Analysis for the Behavioral Sciences (2nd Edition)	Interaction Effects in Logistic Regression (Quantitative Applications in the Social Sciences)

Product Reviews:

OK ( jim28771 )
You need to read Jaccard and Turrisi's Interaction effects in multiple regression before reaing this book. The authors try to get too fancy with a topic that needs to be explained in a straightforward manner. Not too impressed.....

revolutionary ( sleepy_bn )
This book has revolutionized the way psychologists think about interactions. It provides step-by-step instructions on how to probe the moderating effects after you find a significant interaction in a multiple regression.

The basic idea about interaction is that the relationship between two variables were different according to a third variable. For example, some risk factors (such as poor family income) may affect children's academic achievement in a negative way. However, if the parents provide enough support on their children's study, then it's possible that the risk factors will no longer influence their children test scores. Therefore, with low support, risk factors are very effective, but with high support, risk factors have not effects. This book teaches you how to probe this relationship in a systematic way, it covers 2-way, 3-way interactions and also quardratic relationships.

If you fully understand this book, the techniques you have will be enough for a masters thesis in your area.

A MUST have for anyone using regression analysis ( kendemarree )
This book takes a very practical approach to the analysis of interactions in regression. No other book I've used has covered these topics as clearly or in as much depth. The extensive discussion of decomposing interactions is a prime example. With the push to replace old techniques of dichotomizing continuous variables with a continuous (regression) treatment of these variables (especially in psychology), this book is extremely important.

Invaluable and accessible ( chrishart2 )
Back when the book was first published, I was completing doctoral research. Aiken & West provided the explanations and instructions that enabled me to complete my dissertation. Nowhere else have I seen the information they provide; seldom have I seen statistical treatments as clearly and easily explained. Like many in the social sciences, math was not my greatest intellectual ability. This book made computing and understanding regression interactions a relative breeze. One reviewer bemoaned the lack of information on interactions among categorical variables. I suppose he didn't read the preface that specifically explains the reason for the absence: such information is widely available in any good statistical text. What Aiken & West provide can't be found elsewhere in any real depth. I am ordering another copy of the book because I'm tired of loaning out my copy to colleagues, especially one who has now begun to copy whole chapters. Yes, it's that useful.

Lacking
Yes, there is some good information and discussion in this book but for the price I would expect it to be more complete. For example, there is absoultely no mention of interactions between two categorical variables. I guess the authors ran out of steam. Also, the writing could have used some more refinement. I'd stick with Jaccard's volumes in the Sage Quantitative Applications series.

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