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Statistical Models And Causal Inference : A Dialogue With The Social Sciences at Meripustak

Statistical Models And Causal Inference : A Dialogue With The Social Sciences by David A. Freedman , Edited by David Collier , Edited by Jasjeet S. Sekhon , Edited by Philip B. Stark, CAMBRIDGE UNIVERSITY PRESS


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  • General Information  
    Author(s)David A. Freedman , Edited by David Collier , Edited by Jasjeet S. Sekhon , Edited by Philip B. Stark
    PublisherCAMBRIDGE UNIVERSITY PRESS
    ISBN9780521123907
    Pages344
    BindingPaperback
    Language_x000D_English
    Publish YearMarch 2015

    Description

    CAMBRIDGE UNIVERSITY PRESS Statistical Models And Causal Inference : A Dialogue With The Social Sciences by David A. Freedman , Edited by David Collier , Edited by Jasjeet S. Sekhon , Edited by Philip B. Stark

    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 Freedmans views.show more



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