Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences) [Paperback]

James J. Jaccard (Author), Robert Turrisi (Author)

Book Description

Publication Date: March 5, 2003 | ISBN-10: 0761927425 | ISBN-13: 978-0761927426 | Edition: 2nd

Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new addition will expand the coverage on the analysis of three way interactions in multiple regression analysis.

Product Details

• Paperback: 104 pages
• Publisher: Sage Publications, Inc; 2nd edition (March 5, 2003)
• Language: English
• ISBN-10: 0761927425
• ISBN-13: 978-0761927426
• Product Dimensions: 8.3 x 5.5 x 0.3 inches
• Shipping Weight: 4 ounces (View shipping rates and policies)
• Average Customer Review: 4.7 out of 5 stars  See all reviews (3 customer reviews)
• Amazon Best Sellers Rank: #240,563 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

26 of 26 people found the following review helpful:

5.0 out of 5 stars Excellent overview of interactions in regression, December 4, 2004

By 

Amrit Tiwana "www.bus.iastate.edu/tiwana" (Decatur, Georgia, USA) - See all my reviews
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This review is from: Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences) (Paperback)

This is a very nice updated version of the original edition. The book is short at 89 pages, information packed, and solidly grounded. The book is meant for people who *use* interaction effects in thier research. (It is not meant for people who study regression methods.)

STRONG POINTS: It references the key developments in the methodological literature, the most significant of which appeared in Psychological Bulletin. It even discusses in layman terms Chronbach's (of the Chronbach Alpha fame) recent paper in Psyc Bulletin on errors in interactions.

SCOPE: The book covers two-way and three-way interactions. It offers a digestable discussion of variable transformations. The authors clarify two of the biggest misperceptions about testing interactions: (1) It is incorrect to interpret the main effects in the presence of interaction terms and (2) Multicollinearity is rarely a problem with interaction terms if you appropriately transform the variables.

WHAT THE BOOK DOES NOT COVER: The book does not discuss (1) mediation testing and (2) is missing a key reference on that topic. If you're reading this, it will probably be helpful! [1] R. Baron and D. Kenny, "The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations," Journal of Personality and Social Psychology, 51 1986, 1173-1182.

Overall, the book is very well written, readable, and usable in doing interaction analyses. It is meant for the consumer not the producer of statistical methods. SPSS exemplars and detailed interpretations really help clarify the points. For fifteen bucks, this is worth owning, dog-earing, and highlighting. Very highly recommended.

3 of 4 people found the following review helpful:

4.0 out of 5 stars Good, but an overview of which kind of interaction effects are covered would help, July 28, 2009

By 

Lance Peterson - See all my reviews
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This review is from: Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences) (Paperback)

The problem with this book probably has more to do with a widespread problem than the authors. I have thus far found the book to be conceptually clear and concise. (I happen to like James Jaccard's style of explaining statistics; "Statistics for the Behavioral Sciences" (Wadsworth publishing) by Jaccard and Becker is a great beginners statistics book.) Book titles on interaction effects in multiple regression need to be more specific and clear as to what is covered in the text. This book is great for interaction terms for continuous variables, and there is a small section on continuous variables with qualitative variables. However, interactions between two qualitative variables are not adequately covered. I eventually found a book that best covers interactions between two qualitative variables and and between a continuous variable and qualitative variable. It's also in the Sage series and it's by Melissa Hardy, called: "Regression with Dummy Variables". Again, the title of the book gives no one a clue that interaction effects will be covered, but they are! My advice, if you're using interaction in your analyses, is to look carefully at a book's chapter headings to see which interactions are covered in depth.

3 of 7 people found the following review helpful:

5.0 out of 5 stars 6 Stars, July 23, 2006

By 

James Digabriele - See all my reviews
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Amazon Verified Purchase

This review is from: Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences) (Paperback)

If I could, I would give this book an even higher rating! There is no doubt that this is THE BOOK for interaction effects in multiple regession. The authors do a fantastic job with the topic and make sense!