Statistical models and causal inference : a dialogue with the social sciences /

"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 m...

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Bibliographic Details

Main Author:	Freedman, David, 1938-2008
Other Authors:	Collier, David, 1942-, Sekhon, Jasjeet Singh, 1971-, Stark, Philip B.
Format:	Book
Language:	English
Published:	Cambridge ; New York : Cambridge University Press, 2010.
Subjects:	Social sciences > Statistical methods. Linear models (Statistics) Causation. Social sciences.
Online Access:	Online Access Online Access Online Access Notre Dame Online Access
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.