November 2021 Confidence as Likelihood
Yudi Pawitan, Youngjo Lee
Author Affiliations +
Statist. Sci. 36(4): 509-517 (November 2021). DOI: 10.1214/20-STS811


Confidence and likelihood are fundamental statistical concepts with distinct technical interpretation and usage. Confidence is a meaningful concept of uncertainty within the context of confidence-interval procedure, while likelihood has been used predominantly as a tool for statistical modelling and inference given observed data. Here we show that confidence is in fact an extended likelihood, thus giving a much closer correspondence between the two concepts. This result gives the confidence concept an external meaning outside the confidence-interval context, and vice versa, it gives the confidence interpretation to the likelihood. In addition to the obvious interpretation purposes, this connection suggests two-way transfers of technical information. For example, the extended likelihood theory gives a clear way to update or combine confidence information. On the other hand, the confidence connection means that intervals derived from the extended likelihood have the same status as confidence intervals. This gives the extended likelihood direct access to the frequentist probability, an objective certification not directly available to the classical likelihood.

Funding Statement

This research was partly supported by the Korea-Sweden Research Cooperation Grant from the Swedish Foundation for International Cooperation in Research and Higher Education (STINT). Lee’s work was also supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean government (MSIT) (No. 2019R1A2C1002408).


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Yudi Pawitan. Youngjo Lee. "Confidence as Likelihood." Statist. Sci. 36 (4) 509 - 517, November 2021.


Published: November 2021
First available in Project Euclid: 11 October 2021

MathSciNet: MR4323049
zbMATH: 07473932
Digital Object Identifier: 10.1214/20-STS811

Keywords: Confidence density and distribution , Confidence interval , epistemic probability , fiducial probability

Rights: Copyright © 2021 Institute of Mathematical Statistics


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Vol.36 • No. 4 • November 2021
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