A note on p-values interpreted as plausibilities
By Ryan Martin, Chuanhai Liu. 2012
65 citations recorded by the source corpus.
P-values are a mainstay in statistics but are often misinterpreted. We propose a new interpretation of p-value as a meaningful plausibility, where this is to be interpreted formally within the inferential model framework. We show that, for most practical hypothesis testing problems, there exists an inferential model such that the corresponding plausibility function, evaluated at the null hypothesis, is exactly the p-value. The advantages of this representation are that the notion of plausibility is consistent with the way practitioners use and interpret p-values, and the plausibility calculation avoids the troublesome conditioning on the truthfulness of the null. This connection with plausibilities also reveals a shortcoming of standard p-values in problems with non-trivial parameter constraints.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a6bd9763f6a5e5cc1a2ba2b3992429bfaff959fb
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In Management Science and Operations Research
In Statistics and Probability
Citations in the corpus
- An imprecise-probabilistic characterization of frequentist statistical inference (2021, methodology): “Second, the construction in Martin and Liu (2014), which establishes a connection between IM plausibilities and classical p-values, does not involve the fusion step.”