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Rejecting or Accepting Parameter Values in Bayesian Estimation

Bibliographic Data

ID23317320
AuthorsJohn K Kruschke (0000-0003-2001-3485, Indiana University, corresponding author)
Year2018
Volume1
Issue2
Pages270-280
Publication date2018-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAdvances in Methods and Practices in Psychological Science (JOURNAL)
Journal identifiersISSN: 2515-2459 • E-ISSN: 2515-2467
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/2515245918771304
OpenAlexW2801776818
LanguageEN
Citations received109
References cited40

This article explains a decision rule that uses Bayesian posterior distributions as the basis for accepting or rejecting null values of parameters. This decision rule focuses on the range of plausible values indicated by the highest density interval of the posterior distribution and the relation between this range and a region of practical equivalence (ROPE) around the null value. The article also discusses considerations for setting the limits of a ROPE and emphasizes that analogous considerations apply to setting the decision thresholds for p values and Bayes factors.

Algorithm · Bayes factor · Bayes' theorem · Bayesian inference · Bayesian linear regression · Bayesian probability · Credible interval · Econometrics · Null hypothesis · Posterior probability · Range (aeronautics) · Rope · Statistics · Bayesian Modeling and Causal Inference · Computer Science · Engineering · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods in Clinical Trials

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Unique citing works109
Citations per year13,63
Citation span2018 - 2026 (9)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 107

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