(Ebook) Statistical Models and Causal Inference: A Dialogue with the Social Sciences by David A. Freedman; David Collier, Jasjeet S. Sekhon, Philip B. Stark (Editors) ISBN 9780511688836, 9780521123907, 9780521195003, 0511688830, 0521123909, 0521195004, B00E3UR6O6

(Ebook) Statistical Models and Causal Inference: A Dialogue with the Social Sciences by David A. Freedman; David Collier, Jasjeet S. Sekhon, Philip B. Stark (Editors) ISBN 9780511688836, 9780521123907, 9780521195003, 0511688830, 0521123909, 0521195004, B00E3UR6O6

Main subject categories: • Mathematical models • Statistical models • Social sciences ‒ Mathematical models • Causal inference • Mathematical inference • Social sciences ‒ Causal inference • Mathematical inferenceDavid 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 skepticism, 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.