EFFECT size or statistical significance, where to put your money

Mult Scler Relat Disord. 2020 Feb;38:101490. doi: 10.1016/j.msard.2019.101490. Epub 2019 Nov 5.

Abstract

There is continuing controversy over the excessive reliance on p-values. This paper elaborates on the use of p-values, points out their utility and reminds that there is no single measure that is a universal measure of the value of a study. All measures have their warts and moles, but each has utility. This paper discusses not only p-values but important measures of effect, effect sizes. The over or under interpretation of various measures is cautioned. The p-value is just a function of the summary statistic chosen for the outcome, the sample size and indicates a binary decision about the hypothesis. Using p-values are still OK, but should be coupled with other measures, such as effect sizes. A p-value alone won't get you through an ethics review board, no matter what its value, and it shouldn't get you through a journal review either.

Keywords: Effect size; P-values; Testing hypothesis.

MeSH terms

  • Biomedical Research / standards*
  • Data Interpretation, Statistical*
  • Humans
  • Probability*