You notice a minority of scientists were early to advocate: 1. asymptomatic COVID19 occurs 2. masks are useful 3. rapid tests are useful Yet opposition on each came from other scientists. Why? Is it because training has promoted p<0.05 to the point we can't do Baynesian anymore?
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The key to success was clearly being able to distinguish the two. I’m not even sure I’d call it Bayesian. Just matching the right epistemology to the question. MDs think in clinical trials for drugs—appropriately—but that’s not how you figure out aerosols or all public health.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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Whenever I see people demanding RCT for everything, I’m reminded of this paper:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC300808/ …
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good tweet, bad example. parachutes are *extensively* tested before use, with *lots* of data on design and use cases. this discussion is more about acting proactively in the absence of great data.
End of conversation
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