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May 6, 2014 at 22:34 comment added Nick Stauner Nothing on confidence intervals for p values that I recall, but I might've skimmed over those sections. I wasn't interested in making confidence intervals for p values either ;)
May 1, 2014 at 1:40 comment added russellpierce I don't have a citation handy, but I know there is work along those lines - regardless, it is an academic thing to do because you can make confidence intervals of your confidence intervals of your confidence intervals nearly ad infinitum (there is a maximum variance that is reasonably estimated from any set of data). I had a rather long and detailed conversation along these lines with @Nick Stauner once upon a time. He may still have some the articles he dug up during that conversation to bring to the table.
Apr 30, 2014 at 20:56 comment added Peter Flom I have to admit, I hadn't thought of putting confidence intervals (or credibility intervals) around p values. I wonder how much has been done in this area?
Apr 30, 2014 at 20:48 comment added russellpierce In short, it is such a convoluted counter-factual that attempting to quantify a p-value is counter productive when we really should (as you imply) get back to the MAGIC.
Apr 30, 2014 at 20:47 comment added russellpierce We don't often say it, but technically the p-value is only reflecting something about the "probability of getting a test statistic at least as extreme as the one we got in the sample" if the null hypothesis is true, our sample estimate of the population variance is perfectly accurate, and we meet all of the other assumptions of our test. Throw some confidence intervals around some p-values via bootstrapping and I think you'll see that frequently we aren't all that confident about the hundredths place either.
Apr 24, 2014 at 11:36 history answered Peter Flom CC BY-SA 3.0