The headline is broadly defensible, but the qualifications matter. Effect sizes vary by population, the strongest claims rest on shorter trials, and credible voices push back on how it's typically framed.
I tend to find myself looking at the Austin Bradford Hill criteria all the time and for folks who don't know — he was a statistician who basically proposed a set of criteria ... the more of these criteria that that are met within your correlations the more likelihood you will find causality
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Native comments, Twitter mentions, and Reddit threads about this claim — surfaced together so the conversation isn't fragmented across platforms.
Bookmarking — the dossier-vs-overview split is the right call. Most of the time I want overview; sometimes I want receipts.
Would love a "what would change this verdict" RSS feed. Sign me up if it exists.
various factors defined by a a statistician named Austin Bradford Hill speak to the strength of the association and the the probability or likelihood that that Association is causal
Um, we're going to rely on a framework at some point during this discussion um which is very helpful when considering epidemiology which is the branch of science we're going to be talking primarily about today and it's called the Bradford Hill criteria. These are nine principles that were laid out in the mid60s to help us determine whether an observed observation is likely to be causal. Um, so, so this framework looks at things like strength of association, consistency across multiple studies, biologic plausibility, temporality, and things like that.