alt Hacker NewsGood point. Would it be roughly accurate to say: "consider someone who's more depressed than 75% of the *study treated* population becoming completely average *among the study treated population*"?
Good point. Would it be roughly accurate to say: "consider someone who's more depressed than 75% of the *study treated* population becoming completely average *among the study treated population*"?
Nope, you can't say how many people return to average from standardized effect sizes. I wish we had a standardized effect size that was more useful and actually meant something. Cohen actually proposed something called a U3 statistic that told us the percent overlap of two distributions, but that still doesn't tell us anything meaningful about practical significance.
You can't make decisions / determine clinical value from standardized effect sizes sadly, so when I see studies like this, my assumption is unfortunately that the researchers care only about publishing, and not about making their findings useful :(