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Cargando... Statistical Models and Causal Inference: A Dialogue with the Social Sciences (edición 2009)por David A. Freedman, David Collier (Editor), Jasjeet S. Sekhon (Editor), Philip B. Stark (Editor)
Información de la obraStatistical Models and Causal Inference: A Dialogue with the Social Sciences por David Freedman
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Inscríbete en LibraryThing para averiguar si este libro te gustará. Actualmente no hay Conversaciones sobre este libro. Recommended by Mary Anderson, May, 2015. "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 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." From Amazon. ( ) sin reseñas | añadir una reseña
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. No se han encontrado descripciones de biblioteca. |
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Google Books — Cargando... GénerosSistema Decimal Melvil (DDC)519.5Natural sciences and mathematics Mathematics Applied Mathematics, Probabilities Statistical MathematicsClasificación de la Biblioteca del CongresoValoraciónPromedio:
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