Statistical Modeling, Causal Inference, and Social Science
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There’s this well-known—ok, maybe not well-enough known—example where you have a strong linear predictor but R-squared is only 1%. The example goes like this. Consider two states of equal size, one of which is a “blue” state where the Democrats consistently win 55% of the two-party vote and the other which is a “red” state where Republicans win 55-45....
Sponsored by the Alan Turing Institute, the talks will be Thurs 20 June 2024, 5:30pm, at Kings College London. You can register for the event here, and here are the titles and abstracts of the three talks: Beyond the black box: Toward a new paradigm of statistics in science Andrew Gelman Standard paradigms for data-based decision making and policy...
Sociologist Claude Fischer has an interesting review of an edited book, “Myth America: Historians Take On the Biggest Legends and Lies About Our Past.” I’m a big fan of the “Why everything you thought you knew was wrong” genre—it’s a great way to get into the topic. Don’t get me wrong: I’m not a fan of contrarianism for its own sake, especially when...
In her article, “On not sleeping with your students,” philosopher Amia Srinivasan writes that she was struck by “how limited philosophers’ thinking was”: How could the same people who were used to wrestling with the ethics of eugenics and torture (issues you might have imagined were more clear-cut) think that all there was to say about professor-student...
This is Jessica. Conformal prediction, referring to a class of distribution-free approaches to quantifying predictive uncertainty, has attracted interest for medical AI applications. Reasons include because prediction sets seem to align with the kinds of differential diagnoses doctors already use, and they can support common triage decisions like ruling...
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