Clarifying ASA’s View on P-Values in Hypothesis Testing

Abstract

This paper aims at clarifying both the ASA’s Statements on Pvalues (2016) and the recent The American Statistician (TAS) special issue on \Statistical inference in the 21st century: Moving to a world beyond p < 0:05" (2019), as well as the US National Academy of Science’s recent \Reproducibility and Replicability in
Science" (2019). These documents, as a worldwide announcement, put a final end to the use of the notion of P-values in frequentist testing of statistical hypotheses. Statisticians might get the impression that abandoning P-values only affects Fisher’s significance testing, and not NeymanPearson’s (N-P) hypothesis testing since these two \theories" of (frequentist) testing are different, although they are put in a combined testing theory called Null Hypothesis Significance Testing (NHST). Such an impression might be gained because the above documents were somewhat silent on N-P testing, whose main messages are \Don’t say statistically significant" and \Abandon statistical significance". They do not specifically declare \The final collapse of the Neyman-Pearson decision theoretic framework" (as previously presented in Hurlbert and Lombard [14]).
Such an impression is dangerous as it might be thought that N-P
testing is still valid because P-values are not used per se in it