The Ioannidis Affair: A Tale of Major Scientific Overreaction https://bit.ly/3moBjMN Scientific American by @JeanneLenzer1 and @ShannonBrownlee @sdbaral @BMJ_EBM
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Also: "These data are unhelpful because they do not even rule out the null hypothesis that all positives are measurement error" is a very different claim than "I believe that all positives are measurement error".
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Yes. It feels very much as if the authors of this piece did not read the critique of the SC or ask one of the statisticians who made these comments what they meant because what's been printed here is just wildly off-base
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thank you - yes, clearly meant false positives as was argued by critics and I've sent in a correction.
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Changing the word to "positives" leaves the piece incorrect. The issue was with test characteristics - both sensitivity and specificity - and how this impacted the uncertainty of the estimate, not that critics were saying that all tests were definitely false positives
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The key uncertainty about the Santa Clara study was it wasn't randomized - it was publicized on Facebook and people who thought they might have had COVID had every incentive to sign up.
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