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dc.contributor.authorPérez, María Eglée
dc.contributor.authorPericchi Guerra, Luis Raúl
dc.date.accessioned2015-11-21T21:27:54Z
dc.date.available2015-11-21T21:27:54Z
dc.date.issued2014-02
dc.identifier.urihttp://hdl.handle.net/123456789/2405
dc.description.abstractWe put forward an adaptive alpha which changes with the amount of sample information. This calibration may be interpreted as a Bayes–non-Bayes compromise, and leads to statistical consistency. The calibration can also be used to produce confidence intervals whose size takes in consideration the amount of observed information.
dc.description.sponsorshipNIH Grant: P20-RR016470. M.E. Pérez’s research was also sponsored by NSF Grant: HRD 0734826.
dc.language.isoen_US
dc.publisherStatistics & Probability Letters
dc.relation.ispartofseriesVol. 85;
dc.subjectSignificance principle
dc.subjectPosterior probability principle
dc.subjectBayes–non-Bayes compromise
dc.subjectp -value calibration
dc.subjectAdaptive confidence level
dc.titleChanging Statistical Significance with the Amount of Information: The Adaptive α Significance Level
dc.typeArticle


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