
arXiv: 2010.14010
We introduce the notion of p*-values (p*-variables), which generalizes p-values (p-variables) in several senses. The new notion has four natural interpretations: operational, probabilistic, Bayesian, and frequentist. A main example of a p*-value is a mid p-value, which arises in the presence of discrete test statistics. A unified stochastic representation for p-values, mid p-values, and p*-values is obtained to illustrate the relationship between the three objects. We study several ways of merging arbitrarily dependent or independent p*-values into one p-value or p*-value. Admissible calibrators of p*-values to and from p-values and e-values are obtained with nice mathematical forms, revealing the role of p*-values as a bridge between p-values and e-values. The notion of p*-values becomes useful in many situations even if one is only interested in p-values, mid p-values, or e-values. In particular, deterministic tests based on p*-values can be applied to improve some classic methods for p-values and e-values.
38 pages, 5 figures
mid p-values, Bayesian inference, Probability (math.PR), posterior predictive p-values, Mathematics - Statistics Theory, Statistics Theory (math.ST), Parametric hypothesis testing, Paired and multiple comparisons; multiple testing, arbitrary dependence, average of p-values, test martingale, FOS: Mathematics, Inequalities; stochastic orderings, Hypothesis testing in multivariate analysis, Mathematics - Probability
mid p-values, Bayesian inference, Probability (math.PR), posterior predictive p-values, Mathematics - Statistics Theory, Statistics Theory (math.ST), Parametric hypothesis testing, Paired and multiple comparisons; multiple testing, arbitrary dependence, average of p-values, test martingale, FOS: Mathematics, Inequalities; stochastic orderings, Hypothesis testing in multivariate analysis, Mathematics - Probability
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