/articles

    •  :-P

      We are not calling for a ban on P values. Nor are we saying they cannot be used as a decision criterion in certain specialized applications (such as determining whether a manufacturing process meets some quality-control standard). And we are also not advocating for an anything-goes situation, in which weak evidence suddenly becomes credible. Rather, and in line with many others over the decades, we are calling for a stop to the use of P values in the conventional, dichotomous way — to decide whether a result refutes or supports a scientific hypothesis.

      #p-value
      en français on essaye de promouvoir
      #probabilité_associée ( sous-entendu , au rejet de l’hypothèse nulle)

    • résumé de l’article (qui est payant) de The American Statistician

      Why are p-Values Controversial?: The American Statistician: Vol 73, No 1
      https://www.tandfonline.com/doi/abs/10.1080/00031305.2016.1277161

      ABSTRACT
      While it is often argued that a p-value is a probability; see Wasserstein and Lazar, we argue that a p-value is not defined as a probability. A p-value is a bijection of the sufficient statistic for a given test which maps to the same scale as the Type I error probability. As such, the use of p-values in a test should be no more a source of controversy than the use of a sufficient statistic. It is demonstrated that there is, in fact, no ambiguity about what a p-value is, contrary to what has been claimed in recent public debates in the applied statistics community. We give a simple example to illustrate that rejecting the use of p-values in testing for a normal mean parameter is conceptually no different from rejecting the use of a sample mean. The p-value is innocent; the problem arises from its misuse and misinterpretation. The way that p-values have been informally defined and interpreted appears to have led to tremendous confusion and controversy regarding their place in statistical analysis.

    • Ce que j’aime bien dans l’article de Nature, c’est que plus que se débarrasser d’un outil mal-adapté et fétichisé, c’est surtout un appel à la nuance et à la mise en contexte.

      Mais le véritable pouvoir de changement se trouve surtout du côté des éditeurs et des relecteurs ; si les scientifiques doivent danser la gigue de la p-valeur, c’est parce que le système de publication les y oblige, pas parce qu’ils y sont spécialement attachés.
      Il n’y a qu’à voir l’édito dans le même numéro de Nature pour voir que c’est pas gagné :

      There are reasonable viewpoints on all sides; Nature is not seeking to change how it considers statistical analysis in evaluation of papers at this time, but we encourage readers to share their views.

      https://www.nature.com/articles/d41586-019-00874-8

      –-

      A p-value is a bijection of the sufficient statistic for a given test which maps to the same scale as the Type I error probability.

      Ah ben dit comme ça, c’est tout de suite plus clair ! :)