Year: 2022
Type: review
Abstract: For real-valued parameters, significance tests can be motivated as three-decision methods, in which we either assert the sign of the parameter above or below a specified null value, or say nothing either way. Tukey viewed this as a “sensible formulation” of tests, unlike the widely taught null hypothesis significance testing (NHST) system that is today's default. We review the three-decision framework, collecting the substantial literature on how other statistical tools can be usefully motivated in this way. These tools include close Bayesian analogs of frequentist power calculations, p-values, confidence intervals, and multiple testing corrections. We also show how three-decision arguments can straightforwardly resolve some well-known difficulties in the interpretation and criticism of testing results. Explicit results are shown for simple conjugate analyses, but the methods discussed apply generally to real-valued parameters.
Authors: Kenneth M. Rice, Chloe A. Krakauer
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4302759508