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  3. Statistical Models and Causal Inference
  • Cited by 37
Publisher:
Cambridge University Press
Online publication date:
June 2012
Print publication year:
2009
Online ISBN:
9780511815874
DOI:
https://doi.org/10.1017/CBO9780511815874
Subjects:
Statistical Theory and Methods, Statistics and Probability
Information

Book description

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.

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