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  E-mail Message: I thought you might be interested in this item at http://www.worldcat.org/oclc/457770262 Title: Statistical models and causal inference : a dialogue with the social sciences Author: David Freedman; David Collier; Jasjeet Singh Sekhon; Philip B Stark Publisher: Cambridge ; New York : Cambridge University Press, 2010. ISBN/ISSN: 9780521195003 0521195004 9780521123907 0521123909 OCLC:457770262

  
  

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Subjects

• Social sciences -- Statistical methods.
• Linear models (Statistics)
• Causation.
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Statistical models and causal inference : a dialogue with the social sciences

Author:	David Freedman; David Collier; Jasjeet Singh Sekhon; Philip B Stark
Publisher:	Cambridge ; New York : Cambridge University Press, 2010.
Edition/Format:	Book : EnglishView all editions and formats
Summary:	"David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy, law, and epidemiology. Freedman maintains that many new technical approaches to statistical modeling constitute not progress, but regress. Instead, he advocates a 'shoe leather' methodology, which exploits natural variation to mitigate confounding and relies on intimate knowledge of the subject matter to develop meticulous research designs and eliminate rival explanations. When Freedman first enunciated this position, he was met with scepticism, in part because it was hard to believe that a mathematical statistician of his stature would favor 'low-tech' approaches. But the tide is turning. Many social scientists now agree that statistical technique cannot substitute for good research design and subject matter knowledge. This book offers an integrated presentation of Freedman's views"--Provided by publisher.  Read more...
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