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The American Statistician Volume 73, 2019 - Issue sup1: Statistical Inference in the 21st Century: A World Beyond p < 0.05
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Articles

The p-Value Requires Context, Not a Threshold

Rebecca A. BetenskyDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MACorrespondence[email protected]
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Pages 115-117 | Received 15 Mar 2018, Accepted 14 Sep 2018, Published online: 20 Mar 2019

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Usha Govindarajulu. (2023) COVID-19 Research and p-Values. CHANCE 36:3, pages 35-38.
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Xavier Javines Bilon. (2023) Normality and significance testing in simple linear regression model for large sample sizes: a simulation study. Communications in Statistics - Simulation and Computation 52:6, pages 2781-2797.
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Piero Quatto, Enrico Ripamonti & Donata Marasini. (2022) Beyond p < .05: a critical review of new Bayesian proposals for assessing the p-value. Journal of Biopharmaceutical Statistics 32:2, pages 308-329.
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Haolun Shi & Guosheng Yin. (2021) Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests. The American Statistician 75:3, pages 265-275.
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Eric W. Gibson. (2021) The Role of p-Values in Judging the Strength of Evidence and Realistic Replication Expectations. Statistics in Biopharmaceutical Research 13:1, pages 6-18.
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Ronald L. Wasserstein, Allen L. Schirm & Nicole A. Lazar. (2019) Moving to a World Beyond “p < 0.05”. The American Statistician 73:sup1, pages 1-19.
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