Moving beyond p-value
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Scientific literature is overflowing of significance testing and p-values. P-value states how discordant the observed finding is with a null hypothesis. P<0.05 indicates that an association greater than that detected would happen less than 5% of the time under a null hypothesis of no association [...].
Wasserstein R, Lazar N. The ASA’s statement on p-values: context, process, and purpose. Am Stat 2016;70:129-33 DOI: https://doi.org/10.1080/00031305.2016.1154108
Krueger JI, Heck PR. Putting the p-value in its place. Am Stat 2019;73:122-8. DOI: https://doi.org/10.1080/00031305.2018.1470033
Statistical inference in the 21st Century: a world beyond p<0.05. Am Stat 2019;73.
Wasserstein RL, Schirm AL, Lazar NA. Moving to a world beyond p<0.05. Am Stat 2019;73:1-19. DOI: https://doi.org/10.1080/00031305.2019.1583913
Harrington D, D'Agostino RB Sr, Gatsonis C, et al. New guidelines for statistical reporting in the journal. N Engl J Med 2019;381:285-6. DOI: https://doi.org/10.1056/NEJMe1906559
Amrhein V, Greenland S, McShane B. Retire statistical significance. Nature 2019;567:305-7 DOI: https://doi.org/10.1038/d41586-019-00857-9
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