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

This article argues that researchers do not need to completely abandon the p-value, the best-known significance index, but should instead stop using significance levels that do not depend on sample sizes. A testing procedure is developed using a mixture of frequentist and Bayesian tools, with a sign...

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Bibliographic Details

Published in:	American Statistician Vol. 73; pp. 213 - 223
Main Authors:	Gannon, Mark Andrew, de Bragança Pereira, Carlos Alberto, Polpo, Adriano
Format:	Article
Published:	Taylor & Francis Ltd Mar2019 Supplement
Subjects:	Bayesian analysis Statistical significance Hardy-Weinberg formula Neyman-Pearson theorem Sample size (Statistics) Likelihood ratio tests Null hypothesis
Online Access:	View this record in EBSCOhost