Volume 3 • Issue 2 | September 2019
Clarifying ASA’s View on P-Values in Hypothesis Testing
William M. Briggs, Hung T. Nguyen
Bayesian testing
Fisher’s significance testing
Hypothesis testing
LASSO
Linear regression
Neyman-Pearson’s hypothesis test
NHST
P-values
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 Neyman-Pearson’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.
JEL classification: C1, C11, C12