In article <[EMAIL PROTECTED]>,
Will Hopkins <[EMAIL PROTECTED]> wrote:
>I accept that there are unusual cases where the null hypothesis has a
>finite probability of being be true, but I still can't see the point in
>hypothesizing a null, not in biomedical disciplines, anyway.
>If only we could replace the p value with a probability that the true
>effect is negative (or has the opposite sign to the observed effect). The
>easiest way would be to insist on one-tailed tests for everything. Then
>the p value would mean exactly that. An example of two wrongs making a right.
If you want to say something about the probability that
a statement about the state of nature is true, it is
necessary to start with a prior distribution. There
is no controversy about the use of Bayes Theorem to
get posterior distributions.
But this has nothing to do with p values, except that
more extreme values of one in a given situation generally
go with more extreme values of the other in a given
experimental situation. It is not true across situations.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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