The p-value is one of the most common, and one of the most confusing, tools in applied statistics. Seasoned educators are well aware of all the things the p-value is not. Most notably, it’s not “the probability that the null hypothesis is true.” McShane and Gal find that even top researchers routinely misinterpret p-values. But let’s forget for a moment about what p-values are not and instead ask what they are. It turns out that there are different meanings of the term. . . . Definition 1. p-value(y) =

I came across this blog comment from a couple years ago saying that, whatever was going on in the head of Brian “Pizzagate” Wansink when he wrote up those papers with the fake data, in any case his papers papers are not to be believed; they’re a sort of genre fiction. I like this idea, not just the bad science it’s false (hence “fiction,” as in psychologist Stuart Ritchie’s recent book “Science Fictions”), but also that it’s genre fiction; that is, it’s written to a certain pattern, to fulfill certain

I came across an algorithm . . . [follows with description of some classical and Bayesian approaches that use this algorithm] . . . Now the results I have gotten from these models seem very accurate. Is there a theoretical basis for why this model should or shouldn’ t work? I’ m skipping the details so as to emphasize the general nature of my advice on this sort of problem. Here’s how I replied: I am sure you can construct an example where the method under discussion gives bad estimates. That does not

I disagree with Sargent’s statement that “The reason Trump regularly tells lies that are very easy to debunk . . . is to assert the power to say what truth is.” I think it’s simpler than that. People like to say things that make them look better, and this is easier to do if you’ re not constrained by the truth. The big question is not so much why someone who has lied a lot in the past keeps lying — people typically keep doing with what’s worked for them before — but rather why so many of his supporters

This letter by Thorland et al. published in the New England Journal of Medicine is rather amusing. It’s unclear to me what their point is, other than the fact that they find the published results for the new COVID drug molnupiravir “statistically implausible.” Background: The pharma company Merck got very promising results for molnupiravir at their interim analysis (~50% reduction in hospitalisation/death) but less promising results at their final analysis (30% reduction). Thorlund et al. were surprised