This successful book, now available in paperback, provides academics 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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"The book would serve very well as a reference for applied researchers and methodologiests. . . . 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 )About the Author
Stephen G. West (PhD, University of Texas at Austin) is Professor of Quantitative and Social Psychology at the University of Arizona. His current quantitative research interests include field research methods, structural equation modeling, multiple regression analysis, mediational analysis, graphics and exploratory data analysis, and longitudinal data analysis. Current social psychology research interests include personality research, applied social, prevention-related issues in health, mental health. He is the editor of Psychological Methods, published by APA.
Leona S. Aiken (PhD, Purdue University) is Professor and Chair of Social and Quantitative Psychology at Arizona State University. Her research interests include both quantitative methods and health psychology. In quantitative methods, she is known for her work in continuous variable interactions in multiple regression. She is also interested in the use of design approaches and mediational analysis to untangle the effects of individual components in multi-component interventions. In health psychology, she is interested in adoption of health protective behaviors across the life span, particularly among women, both from the perspectives of psychosocial models of the putative determinants of health protective behavior and from the perspective of interventions to increase health protective behavior.
Leona S. Aiken (PhD, Purdue University) is Professor and Chair of Social and Quantitative Psychology at Arizona State University. Her research interests include both quantitative methods and health psychology. In quantitative methods, she is known for her work in continuous variable interactions in multiple regression. She is also interested in the use of design approaches and mediational analysis to untangle the effects of individual components in multi-component interventions. In health psychology, she is interested in adoption of health protective behaviors across the life span, particularly among women, both from the perspectives of psychosocial models of the putative determinants of health protective behavior and from the perspective of interventions to increase health protective behavior.
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Most Helpful Customer Reviews
6 of 7 people found the following review helpful
By A Customer
Format:Paperback
This book provides a systematic approach to analysing and interpreting interactions in regression. Whether it is an interaction between two categorical variables, one continuous with one categorical variable etc - they have it in this book! Many examples are given as well as the computational procedures demonstrated. As interactions are part and parcel of regression analysis, a book specially devoting to this topic becomes indispensible. The book is well organised and is very useful as a reference guide as well.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
4.3 out of 5 stars
11 reviews
9 of 9 people found the following review helpful
5.0 out of 5 stars
Invaluable and accessible
2 Oct 2002
By Christian Hart
- Published on Amazon.com
Format:Paperback
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.
8 of 8 people found the following review helpful
4.0 out of 5 stars
one-step guide to interaction effect
4 April 2000
By A Customer
- Published on Amazon.com
Format:Paperback
A colleague recommanded this book, when I was struggling with multip-effect interaction. The book proved to be an apt and excellent choice for this kind of problem. There are several chapters detailing the interactions, unlike many other regression textbooks, which tend to skim over this subject. If the authors could be more succint in their writing, this book would have definitely deserved a 5-star.
7 of 7 people found the following review helpful
5.0 out of 5 stars
revolutionary
3 July 2003
By sleepy_bn
- Published on Amazon.com
Format:Paperback
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.
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4.3 out of 5 stars
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