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 ma...

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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: eBook
Language:English
Published: Cambridge Cambridge University Press 2009
Links:https://doi.org/10.1017/CBO9780511815874
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.
Physical Description:1 Online-Ressource (xvi, 399 Seiten)
ISBN:9780511815874