by ButterflyEffect

Unfortunately, of course, most effect sizes are not factor of 20. Indeed, they are usually less than a factor of 2. As we saw in the mask study, the effect size was less than a factor of 1.1. I’m picking on the mask study only because it has been so attention grabbing. It’s a convenient example to illustrate how statistical modeling can muddy the waters in randomized control trials. But it is only one of many examples I’ve come across in the past few months. If you pick a random paper out of the New England Journal of Medicine or the American Economic Review, you will likely find similar statistical muddiness.

Smart denizens of Hubski, what are your thoughts?