Stop estimating post hoc power! [Power / Sample Size]

posted by ElMaestro  – Denmark, 2017-12-26 14:11  – Posting: # 18087
Views: 18,795

Hi kms.srinivas,

I know this post-hoc power business can be very tricky.

Try and ask yourself which question post-hoc power actually answers. Try and formulate it in a very specific sentence.

Generally, [given a statistical model] power is the chance of showing BE in a trial if your expectations about GMR, CV are correct when you use N subjects.
Choice of GMV, CV and N to plug in a power calculation is up to the user, but in the specific case of post-hoc power stats software may make such a choice for you without asking. Often it is 95% or 100% regardless of what you observed in the previous trial.

So with this in mind try and look back in your figures and tell which question the post-hoc calculation in your case gave an answer to. Feel free to paste your numbers here then I am sure someone can help working it out. You might get surprised.:-)

if (3) 4

x=c("Foo", "Bar")
typeof(b[,1]) ##aha, integer?
b[,1]+1 ##then let me add 1

Best regards,

“(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures.” New York Times (ed.), June 9, 2018.

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