This morning I received a paper I have been asked to review (anonymously as is typical). It is to head up a forthcoming issue of a new journal called Philosophy of Statistics: Retraction Watch. This is the first I’ve heard of the journal, and I plan to recommend they publish the piece, conditional on revisions. I thought I would post the abstract here. It’s that interesting.
“Some Slightly More Realistic Self-Criticism in Recent Work in Philosophy of Statistics,” Philosophy of Statistics: Retraction Watch, Vol. 1, No. 1 (2012), pp. 1-19.
In this paper we delineate some serious blunders that we and others have made in published work on frequentist statistical methods. First, although we have claimed repeatedly that a core thesis of the frequentist testing approach is that a hypothesis may be rejected with increasing confidence as the power of the test increases, we now see that this is completely backwards, and we regret that we have never addressed, or even fully read, the corrections found in Deborah Mayo’s work since at least 1983, and likely even before that.
Second, we have been wrong to claim that Neyman-Pearson (N-P) confidence intervals are inconsistent because in special cases it is possible for a specific 95% confidence interval to be known to be correct. Not only are the examples required to show this absurdly artificial, but the frequentist could simply interpret this “vacuous interval” “as a statement that all parameter values are consistent with the data at a particular level,” which, as Cox and Hinkley note, is an informative statement about the limitations in the data (Cox and Hinkley 1974, 226). Continue reading
Error Statistics Philosophy 