Category: Miscellaneous Statistics

My talk tomorrow (Tues) noon at the Princeton University Psychology Department

Integrating collection, analysis, and interpretation of data in social and behavioral research Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University The replication crisis has made us increasingly aware of the flaws of conventional statistical reasoning based on hypothesis testing. The problem is not just a technical issue with p-values, not can […]

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Stephen Wolfram explains neural nets

It’s easy to laugh at Stephen Wolfram, and I don’t like some of his business practices, but he’s an excellent writer and is full of interesting ideas. This long introduction to neural network prediction algorithms is an example. I have no idea if Wolfram wrote this book chapter himself or if he hired one of […]

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These 3 problems destroy many clinical trials (in context of some papers on problems with non-inferiority trials, or problems with clinical trials in general)

Paul Alper points to this news article in Health News Review, which says: A news release or story that proclaims a new treatment is “just as effective” or “comparable to” or “as good as” an existing therapy might spring from a non-inferiority trial. Technically speaking, these studies are designed to test whether an intervention is […]

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Hey, check this out: Columbia’s Data Science Institute is hiring research scientists and postdocs!

Here’s the official announcement: The Institute’s Postdoctoral and Research Scientists will help anchor Columbia’s presence as a leader in data-science research and applications and serve as resident experts in fostering collaborations with the world-class faculty across all schools at Columbia University. They will also help guide, plan and execute data-science research, applications and technological innovations […]

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Robustness checks are a joke

Someone pointed to this post from a couple years ago by Uri Simonsohn, who correctly wrote: Robustness checks involve reporting alternative specifications that test the same hypothesis. Because the problem is with the hypothesis, the problem is not addressed with robustness checks. Simonsohn followed up with an amusing story: To demonstrate the problem I [Simonsohn] […]

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Hey! Here’s what to do when you have two or more surveys on the same population!

This problem comes up a lot: We have multiple surveys of the same population and we want a single inference. The usual approach, applied carefully by news organizations such as Real Clear Politics and Five Thirty Eight, and applied sloppily by various attention-seeking pundits every two or four years, is “poll aggregation”: you take the […]

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Watch out for naively (because implicitly based on flat-prior) Bayesian statements based on classical confidence intervals! (Comptroller of the Currency edition)

Laurent Belsie writes: An economist formerly with the Consumer Financial Protection Bureau wrote a paper on whether a move away from forced arbitration would cost credit card companies money. He found that the results are statistically insignificant at the 95 percent (and 90 percent) confidence level. But the Office of the Comptroller of the Currency […]

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