Statistical Models and Causal Inference
Statistical Models and Causal Inference David A. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy,…
Specifikacia Statistical Models and Causal Inference
Statistical Models and Causal Inference
David A. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy, law, and epidemiology. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences.
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. Freedman maintains that many new technical approaches to statistical modeling constitute not progress, but regress. 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
Causal Inference
Causal Inference: The Mixtape
Fundamentals of Causal Inference
Explanation in Causal Inference