Statistical Science

On the Birnbaum Argument for the Strong Likelihood Principle

Deborah G. Mayo

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Abstract

An essential component of inference based on familiar frequentist notions, such as $p$-values, significance and confidence levels, is the relevant sampling distribution. This feature results in violations of a principle known as the strong likelihood principle (SLP), the focus of this paper. In particular, if outcomes $\mathbf{x}^{\ast }$ and $\mathbf{y}^{\ast }$ from experiments $E_{1}$ and $E_{2}$ (both with unknown parameter $\theta $) have different probability models $f_{1}(\cdot)$, $f_{2}(\cdot)$, then even though $f_{1}(\mathbf{x}^{\ast };\theta )=cf_{2}(\mathbf{y}^{\ast };\theta )$ for all $\theta $, outcomes $\mathbf{x}^{\ast }$ and $\mathbf{y}^{\ast }$ may have different implications for an inference about $\theta $. Although such violations stem from considering outcomes other than the one observed, we argue this does not require us to consider experiments other than the one performed to produce the data. David Cox [Ann. Math. Statist. 29 (1958) 357–372] proposes the Weak Conditionality Principle (WCP) to justify restricting the space of relevant repetitions. The WCP says that once it is known which $E_{i}$ produced the measurement, the assessment should be in terms of the properties of $E_{i}$. The surprising upshot of Allan Birnbaum’s [J. Amer. Statist. Assoc. 57 (1962) 269–306] argument is that the SLP appears to follow from applying the WCP in the case of mixtures, and so uncontroversial a principle as sufficiency (SP). But this would preclude the use of sampling distributions. The goal of this article is to provide a new clarification and critique of Birnbaum’s argument. Although his argument purports that [(WCP and SP) entails SLP], we show how data may violate the SLP while holding both the WCP and SP. Such cases also refute [WCP entails SLP].

Article information

Source
Statist. Sci., Volume 29, Number 2 (2014), 227-239.

Dates
First available in Project Euclid: 18 August 2014

Permanent link to this document
https://projecteuclid.org/euclid.ss/1408368573

Digital Object Identifier
doi:10.1214/13-STS457

Mathematical Reviews number (MathSciNet)
MR3264534

Zentralblatt MATH identifier
1332.62025

Keywords
Birnbaumization likelihood principle (weak and strong) sampling theory sufficiency weak conditionality

Citation

Mayo, Deborah G. On the Birnbaum Argument for the Strong Likelihood Principle. Statist. Sci. 29 (2014), no. 2, 227--239. doi:10.1214/13-STS457. https://projecteuclid.org/euclid.ss/1408368573


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See also

  • Discussion of: On the Birnbaum Argument for the Strong Likelihood Principle.
  • Discussion of: On the Birnbaum Argument for the Strong Likelihood Principle.
  • Discussion: Foundations of Statistical Inference, Revisited.
  • Discussion: On Arguments Concerning Statistical Principles.
  • Discussion of: On the Birnbaum Argument for the Strong Likelihood Principle.
  • Discussion of: On the Birnbaum Argument for the Strong Likelihood Principle.
  • Rejoinder: On the Birnbaum Argument for the Strong Likelihood Principle.