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  2. Miguel Hernán - Wikipedia

    en.wikipedia.org/wiki/Miguel_Hernán

    His book Causal Inference: What If, [3] co-authored with James Robins is also freely available online and widely used for the training of researchers. Hernán is a Methods Editor for Annals of Internal Medicine , Editor Emeritus of Epidemiology (journal) and past Associate Editor of Biometrics (journal) , American Journal of Epidemiology , and ...

  3. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.

  4. Causality (book) - Wikipedia

    en.wikipedia.org/wiki/Causality_(book)

    Causality: Models, Reasoning, and Inference (2000; [1] updated 2009 [2]) is a book by Judea Pearl. [3] It is an exposition and analysis of causality. [4] [5] It is considered to have been instrumental in laying the foundations of the modern debate on causal inference in several fields including statistics, computer science and epidemiology. [6]

  5. Rubin causal model - Wikipedia

    en.wikipedia.org/wiki/Rubin_causal_model

    Rubin defines a causal effect: Intuitively, the causal effect of one treatment, E, over another, C, for a particular unit and an interval of time from to is the difference between what would have happened at time if the unit had been exposed to E initiated at and what would have happened at if the unit had been exposed to C initiated at : 'If an hour ago I had taken two aspirins instead of ...

  6. Lord's paradox - Wikipedia

    en.wikipedia.org/wiki/Lord's_paradox

    Unlike descriptive statements (e.g. "the average height in the US is X"), causal statements involve a comparison between what happened and what would have happened absent an intervention. The latter is unobservable in the real world, a fact that Holland & Rubin term "the fundamental problem of causal inference" (pg. 10).

  7. Judea Pearl - Wikipedia

    en.wikipedia.org/wiki/Judea_Pearl

    He is one of the founding editors of the Journal of Causal Inference. Pearl is currently a professor of computer science and statistics and director of the Cognitive Systems Laboratory at UCLA. He and his wife, Ruth, had three children. In addition, as of 2011, he is a member of the International Advisory Board of NGO Monitor. [13]

  8. The Book of Why - Wikipedia

    en.wikipedia.org/wiki/The_Book_of_Why

    The Book of Why: The New Science of Cause and Effect is a 2018 nonfiction book by computer scientist Judea Pearl and writer Dana Mackenzie. The book explores the subject of causality and causal inference from statistical and philosophical points of view for a general audience.

  9. Scott Cunningham (economist) - Wikipedia

    en.wikipedia.org/wiki/Scott_Cunningham_(economist)

    The content focuses on causal inference, a set of statistical and econometric techniques designed to isolate and measure causal effects, even in situations in which a randomized experiment is not possible. Cunningham's textbook is intended to bridge the gap between high-level theory and research and practical application.