How to measure effect sizes for rational decision-making

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Abstract
Absolute and relative outcome measures measure a treatment’s effect size, purporting to inform treatment choices. I argue that absolute measures are at least as good as, if not better than, relative ones for informing rational decisions across choice scenarios. Specifically, this dominance of absolute measures holds for choices between a treatment and a control group treatment from a trial and for ones between treatments tested in different trials. This distinction has hitherto been neglected, just like the role of absolute and baseline risks in decision-making that my analysis reveals. Recognizing both aspects advances the discussion on reporting outcome measures.
Abstract ID :
PSA2022385
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Associated Sessions

Speaker
,
University of Cambridge

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