{
  "$type": "site.standard.document",
  "path": "/t/fda-draft-guidance-use-of-bayesian-methodology-in-clinical-trials-of-drug-and-biological-products/28598#post_7",
  "publishedAt": "2026-02-04T16:42:53.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "Pavlos the points you raised are the key ones to express extreme concern about in the EMA document. Behind the scenes is the fact that while frequentists are always asking Bayesians to simulate frequentist operating characteristics, Bayesian never ask frequentists to simulate Bayesian operating characteristics. Had this been commonplace, we would have ample demonstrations of why it’s a bad idea to control a transposed-conditional probability. This reminds me of an episode of _The Office_ where one team of office workers wins a trivia contest at a party and the other team, of which the boss is a member, demands that to get the prize the first team must also win a “shoe toss over the roof” contest.\n\nPractically speaking, for many applications frequentist methods will be relatively OK when strong frequentist evidence for an effect is found, when one does not care about clinical significance. But the sample size needed by the frequentist method will be too large or with sequential testing the frequentist approach will take too long in achieving a result. If one is interesting in abandoning ineffective treatments early, frequentist methods will take **way too long**.",
  "title": "FDA Draft Guidance: Use of Bayesian Methodology in Clinical Trials of Drug and Biological Products"
}