On Thu, 16 Oct 2003 18:38:20 GMT, DZ <[EMAIL PROTECTED]> wrote: >Enda Kelly <[EMAIL PROTECTED]> wrote: > >> Hi. I have a query regarding whether it is logical to place a >> confidence interval about a P-value. The computation involved uses a >> permutation method to produce a P-value for a hypothesis test. > >Variance associated with the estimate of such P-value will be >proportional to p(1-p) where p is the "true" p - which can be defined >as p obtained with the infinite number of permutations.
That doesn't make sense. Why would an infinite number of permutations give a "true" p-value? The p-value is the probability that data following a hypothesized distribution would give a value of a discrepancy measure that meets or exceeds the one you observed. If you have a point null hypothesis and it's true, then the p-value should have a Uniform (0,1) distribution, no matter what the sample size. If the alternative is true and you consider it fixed while you look at larger and larger sample sizes, then you'd expect the p-value to tend to zero. So in answer to the original query, no, confidence intervals for p-values don't make sense. Confidence intervals make sense when there is some true fixed value and you're constructing a random interval which has certain coverage properties in repeated sampling. They don't make sense conditional on one particular dataset. Duncan Murdoch . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
