Discussion about this post

User's avatar
Frank Harrell's avatar

I think that there were many papers about this case in Statistics in Medicine. This case is all about the illogic of multiplicity adjustments when one wants to ask specific questions about specific endpoints. Other than in frequentist statistics, rules of evidence are much clearer than this discussion would have you believe. For example, if the police decide that the first suspect in a crime is not the best suspect and they arrest a second person, there is no logic in downweighting the fingerprint and motives of the 2nd suspect just because there was an earlier suspect. Evidence of guild for the 2nd suspect must come from evidence about THAT suspect and the detective’s prior beliefs. The logical Bayesian approach would be to formulate prior distributions of effects of the drug, separately for each endpoint, before data are available. Then apply those priors to the data and don’t look back. Even better: create a hierarchical ordinal endpoint for judging which group of patients fared better overall. Death would be at the top of the scale, and the ordinal analysis would penalize or reward for death even though the sample size may have been inadequate for judging mortality on its own.

Expand full comment
JDK's avatar

Let's get philosphical Dr. Mandrola.

Here is a study:

standard of care plus placebo "b" (blue and smaller pill)

vs.

standard of care plus placebo "R" (red and bigger pill)

Placebo "b" 7.8% deaths (out of 400)

Placebo "R" 3.1% deaths (out of 700)

Is it a "no brainer" to start using Placebo "R"? Why? I suppose that depends on what we mean by "no brainer".

Placebo "b" costs $0.01, Placebo "R" costs $20.00. Now what?

Expand full comment
18 more comments...

No posts