Rejecting or Accepting Parameter Values in Bayesian Estimation

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 bet...

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Veröffentlicht in:Advances in methods and practices in psychological science 2018-06, Vol.1 (2), p.270-280
1. Verfasser: Kruschke, John K.
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:2515-2459
2515-2467
DOI:10.1177/2515245918771304