The evidence is convergent. Multiple independent sources reach the same conclusion, the underlying mechanism is well-characterized, and even the field's most cautious voices treat it as worth doing.
when a study is overpowered and now you have more people in the study than you should have had for the effect size and you start to find things that are statistically significant but are probably irrelevant clinically so you that's when you start to pick up an effect size of one percent when you're dealing with something clinically that should never be thought of as being relevant below 10 detection threshold
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Bookmarking — the dossier-vs-overview split is the right call. Most of the time I want overview; sometimes I want receipts.
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so so sort of data mining studies where they're you know grossly overpowered
and now you have more people in the study than you should have had for the effect size and you start to find things that are statistically significant but are probably irrelevant clinically so you that's when you start to pick up an effect size of one percent when you're dealing with something clinically that should never be thought of as being relevant below 10 detection threshold
what if you overpower power a study in other words what if the power analysis says to be uh to have a level of power at 90% you need a th subjects and you Sayre we're going to do 10,000 subjects well you're clearly powered for it but you might be overpowered and people might say well why would that be a bad thing it could be a bad thing because it means you are very likely to reach statistical significance in things that might not be actually significant