Open Access
May 2014 Discussion: Foundations of Statistical Inference, Revisited
Ryan Martin, Chuanhai Liu
Statist. Sci. 29(2): 247-251 (May 2014). DOI: 10.1214/14-STS472

Abstract

This is an invited contribution to the discussion on Professor Deborah Mayo’s paper, “On the Birnbaum argument for the strong likelihood principle,” to appear in Statistical Science. Mayo clearly demonstrates that statistical methods violating the likelihood principle need not violate either the sufficiency or conditionality principle, thus refuting Birnbaum’s claim. With the constraints of Birnbaum’s theorem lifted, we revisit the foundations of statistical inference, focusing on some new foundational principles, the inferential model framework, and connections with sufficiency and conditioning.

Citation

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Ryan Martin. Chuanhai Liu. "Discussion: Foundations of Statistical Inference, Revisited." Statist. Sci. 29 (2) 247 - 251, May 2014. https://doi.org/10.1214/14-STS472

Information

Published: May 2014
First available in Project Euclid: 18 August 2014

zbMATH: 1332.62024
MathSciNet: MR3264537
Digital Object Identifier: 10.1214/14-STS472

Keywords: Birnbaum , Conditioning , Dimension reduction , inferential model , likelihood principle

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.29 • No. 2 • May 2014
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