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Regression Analysis: A Constructive Critique (Advanced Quantitative Techniques in the Social Sciences) (v. 11) Hardcover – July 17, 2003

ISBN-13: 978-0761929048 ISBN-10: 0761929045 Edition: 1st
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Regression Analysis: A Constructive Critique (Advanced Quantitative Techniques in the Social Sciences) (v. 11) + Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
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Editorial Reviews

Review

"Berk has incisively identified the various strains of regression abuse and suggests practical steps for researchers who desire to do good social science while avoiding such errors."

(Peter H. Rossi)

"I have been waiting for a book like this for some time. Practitioners, especially those doing applied work, will have much to gain from Berk's volume, regardless of their level of statistical sophistication. Graduate students in sociology, education, public policy, and any number of similar fields should also use it. It will also be a useful foil for conventional texts for the teaching of the regression model. I plan to use it for my students as a text, and hope others will do the same."

(Herbert Smith)

"An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students."

(David A. Freedman)

"This book lives up to its subtitle as a "constructive critique" that complements the more standards "how-to" treatments of regression, and I hope that many students and practitioners will be inspired by it to think harder about the connections between their data analysis, their statistical models, and their social science research goals." ―CRIMINAL JUSTICE REVIEW (Andrew E. Gelman 2007-06-21)
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Product Details

  • Series: Advanced Quantitative Techniques in the Social Sciences (Book 11)
  • Hardcover: 280 pages
  • Publisher: SAGE Publications, Inc; 1 edition (July 17, 2003)
  • Language: English
  • ISBN-10: 0761929045
  • ISBN-13: 978-0761929048
  • Product Dimensions: 6 x 0.8 x 9 inches
  • Shipping Weight: 13.6 ounces (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #775,854 in Books (See Top 100 in Books)

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12 of 12 people found the following review helpful By Alexander C. Zorach on December 12, 2007
Format: Hardcover
This book is a must-read for any statistician or researcher in the social science who desires to use regression in their work, or to interpret or critique others' work that makes use of regression. The focus of the book is on identifying the potential for abuse of regression and finding ways to use regression effectively without abusing it. This book is extremely disciplined in its philosophical approach and aims to cultivate that same critical outlook in others. This book has two notable weaknesses, however: the author offers neither creativity nor encouragement when it comes to exploring new techniques. Also, the author makes almost exclusive use of fabricated data, instead of real data, to illustrate his points.

The author claims that this book would be most useful for people with prior background in regression, but I find this book to be quite accessible. If anything, the author may slightly exaggerate the prerequisites (in the interest of caution and rigor), and in addition to this, he makes up for the subtle and difficult nature of the material through his excellent writing style. In the end, though, this book is more difficult on a philosophical than a mathematical level; this book requires deep thought and self-motivation to understand, but not much in the way of mathematical background.

The core message of this book is that regression has the greatest potential as a descriptive and data-analytic technique, and that its use in inference, particularly in causal inference, is almost always misguided. It is hard to disagree with the author's viewpoint without being in rather severe denial of reality; the author's criticisms are very sound, regardless of whether they are what most statisticians or social scientists "want to hear".
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1 of 4 people found the following review helpful By David Zes on March 2, 2006
Format: Hardcover
Emphasizes concepts and conditions underlying good regression. While typical books on regression hurl equations at you, this book details the meaningfulness of various model assumptions.
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