In science publishing and many areas of research, we have reached a ‘binary decision rule’ in which any result is first required to have a p-value that surpasses the 0.05 threshold and only then is consideration given to such results as strong evidence in favor of a scientific theory.
There have been recent proposals to change the p-value threshold, but instead the authors of this paper recommend abandoning the null hypothesis significance testing paradigm entirely, leaving p-values as just one of many pieces of information with no privileged role in scientific publication and decision making. McShane and colleagues argue that this radical approach will have a salutary effect of pushing researchers away from the pursuit of irrelevant statistical targets and toward understanding of theory, mechanism, and measurement. They also hope that this will push scientists to move beyond binary statements about there being ‘an effect’ or ‘no effect’, to one routine of continuous and inevitably flawed learning that is accepting uncertainty and variation.