Abstract:

Statistical hypothesis testing and the associated Pvalue are at the heart of empirical evidence sciences and yet several prominent statisticians recently warn the widespread abuse of the Pvalue and its contribution to false positive findings. The current discussion follows up a paper of the same author "The Pvalue you can't buy" and suggests an alternative, called the Dvalue, which has a more clear interpretation. Unlike the Pvalue, the new measure does not decrease to zero when the sample size, n, goes to infinity. The Dvalue is computed by the same formula as the Pvalue but uses n=1, and therefore may be viewed as the nof1 Pvalue. The Dvalue is at the crossroads of major statistical concepts such as the area under ROC curve, MannWhitney U test, and effect size. It has a clear interpretation as the probability that a randomly chosen patient from the treatment group gets worse than a randomly chosen patient from the placebo group. Thus, unlike Pvalue with the emphasis on the average, Dvalue reflects the individual comparison. The Dvalue is in unison with the voices from medical doctors: "We treat not a group of patients but an individual."
