5/n So what we do instead is weight the studies This is our meta-analytic model - a *weighted* average that gives more weight to bigger/better studies
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One way to try and think about this is to look at the included estimates and think about what that weighted average means for each of them. Does it mean a % reduction in death? Does that same % apply to symptoms? If we analyse only one of those, would we get the same result?
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For sure can't *fully* believe these RR. But when 1 study finds seatbelts reduce deaths by x% (but p>0.05), and a 2nd finds they reduce hospitalization by y% (also p>0.05), would you dismiss seatbelts? When maybe the combined "prevent-damage-score" was stat.sig.
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at least that works out unit-wise, in contrast to the complete clownerie you implied above!
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In practice it gets you a number that seems on face value to be more useful but actually makes just as little sense. That's what I was trying to get at
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