Here's another installment of rationality quotes. The usual rules apply:
- Please post all quotes separately, so that they can be upvoted or downvoted separately. (If they are strongly related, reply to your own comments. If strongly ordered, then go ahead and post them together.)
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Have you read the study in question? The treatment sample is NOT several thousand, its about 1500. Further, the incidence of the diseases being looked at are only a few percent or less, so the treatment sample sizes for the most prevalent diseases are around 50 (also, if you look at the specifics of the sample, the diseased groups are pretty well controlled).
I suggest the following exercise- ask yourself what WOULD be a big effect, and then work through if the study has the power to see it.
Yes, but in this case, the sample sizes are small and the error bars are so large that consistent with zero is ALSO consistent with 25+ % reduction in incidence (which is a large intervention). The study is incapable from distinguishing hugely important effect from 0 effect, so we shouldn't update much at all, which is why I wished Mcardle had talked about statistical power. Before we ask "how should we update", we should ask "what information is actually here?"
Edit: If we treat this as an exploration, it says "we need another study"- after all the effects could be as large as 40%! Thats a potentially tremendous intervention. Unfortunately, its unethical to randomly boot people off of insurance so we'll likely never see that study done.