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Beyond p < .05: a critical review of new Bayesian proposals for assessing the p-value.
Quatto, Piero; Ripamonti, Enrico; Marasini, Donata.
  • Quatto P; Department of Economics, Management and Statistics, Statistical Section, University of Milan-Bicocca, Milan, Italy.
  • Ripamonti E; Milan Center of Neuroscience, University of Milan-Bicocca, Milan, Italy.
  • Marasini D; Milan Center of Neuroscience, University of Milan-Bicocca, Milan, Italy.
J Biopharm Stat ; 32(2): 308-329, 2022 03.
Article in English | MEDLINE | ID: covidwho-2187311
ABSTRACT
This paper reviews recent contributions from a Bayesian-oriented perspective, after the ASA statement on p-values (2016). We classify proposals that (i) supplement the p-value; (ii) modify the p-value itself. In the first group, we review the Bayes factor, the False Positive risk, the rejection odds and the analysis of credibility from both Matthews' and Held's point of view. We also put forth and discuss a new index of credibility, about which we conduct a delimited simulation study. In the second group, we discuss Gannon's modification of the p-value based on the Bayes factor and the second-generation p-value. The theory is illustrated with two case studies on pharmacotherapy in infectious diseases. Contemporary authors still refer to the p-value as a statistical indicator but have abandoned the perspective of evaluating p-values with fixed thresholds. Statistical societies worldwide should target new strategies to disseminate the debate on p-values in all applied fields of knowledge, as well as they may promote the use of different statistical procedures to supplement p-values.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Bayes Theorem Type of study: Experimental Studies / Prognostic study / Reviews Limits: Humans Language: English Journal: J Biopharm Stat Journal subject: Pharmacology Year: 2022 Document Type: Article Affiliation country: 10543406.2021.2009497

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Bayes Theorem Type of study: Experimental Studies / Prognostic study / Reviews Limits: Humans Language: English Journal: J Biopharm Stat Journal subject: Pharmacology Year: 2022 Document Type: Article Affiliation country: 10543406.2021.2009497