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Zbl 1048.62006
Berger, James O.
Could Fisher, Jeffreys and Neyman have agreed on testing? (With comments and a rejoinder). (English)
[J] Stat. Sci. 18, No. 1, 1-32 (2003). ISSN 0883-4237

Summary: Ronald Fisher advocated testing using p-values, Harold Jeffreys proposed use of objective posterior probabilities of hypotheses, and Jerzy Neyman recommended testing with fixed error probabilities. Each was quite critical of the other approaches. Most troubling for statistics and science is that the three approaches can lead to quite different practical conclusions. \par This article focuses on discussion of the conditional frequentist approach to testing, which is argued to provide the basis for a methodological unification of the approaches of Fisher, Jeffreys and Neyman. The idea is to follow Fisher in using p-values to define the ``strength of evidence" in data and to follow his approach of conditioning on strength of evidence; then follow Neyman by computing Type I and Type II error probabilities, but do so conditional on the strength of evidence in the data. The resulting conditional frequentist error probabilities equal the objective posterior probabilities of the hypotheses advocated by Jeffreys.

MSC 2000:: *62A01 Foundational and philosophical topics
62-03 Historical (statistics)
62F03 Parametric hypothesis testing
01A60 Mathematics in the 20th century

Keywords: conditional testing

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