Blending Bayesian and Classical Tools to Define Optimal Sample-Size-Dependent Significance Levels

DOI10.1080/00031305.2018.1518268OpenAlexW2923170007MaRDI QIDQ5868254

Adriano Polpo, Mark Andrew Gannon, Carlos Alberto de Bragança Pereira

Publication date: 20 September 2022

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2018.1518268

zbMATH Keywords

Neyman-Pearson lemmapredictive distributionHardy-Weinberg equilibriumsignificance test

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Comparative Probability Metrics: Using Posterior Probabilities to Account for Practical Equivalence in A/B tests ⋮ New Bayesian approaches to equivalence testing ⋮ Moving to a World Beyond “p < 0.05”

Cites Work

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• Testing precise hypotheses. With comments and a rejoinder by the authors
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• A STATISTICAL PARADOX
• A comment on D. V. Lindley's statistical paradox
• On the Foundations of Statistical Inference
• Inference for a Bernoulli Process (A Bayesian View)
• Bayes Factors
• Sequential Trials, Sequential Analysis and the Likelihood Principle
• The ASA Statement on p-Values: Context, Process, and Purpose
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