Conflicts in Bayesian Statistics Between Inference Based on Credible Intervals and Bayes Factors

Miodrag Lovric
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引用次数: 8

Abstract

In frequentist statistics, point-null hypothesis testing based on significance tests and confidence intervals are harmonious procedures and lead to the same conclusion. This is not the case in the domain of the Bayesian framework. An inference made about the point-null hypothesis using Bayes factor may lead to an opposite conclusion if it is based on the Bayesian credible interval. Bayesian suggestions to test point-nulls using credible intervals are misleading and should be dismissed. A null hypothesized value may be outside a credible interval but supported by Bayes factor (a Type I conflict), or contrariwise, the null value may be inside a credible interval but not supported by the Bayes factor (Type II conflict). Two computer programs in R have been developed that confirm the existence of a countable infinite number of cases, for which Bayes credible intervals are not compatible with Bayesian hypothesis testing.
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贝叶斯统计中基于可信区间推断与贝叶斯因子的冲突
在频率统计中,基于显著性检验和置信区间的点零假设检验是和谐的过程,得出的结论是一致的。在贝叶斯框架的领域中,情况并非如此。利用贝叶斯因子对点零假设进行推断,如果基于贝叶斯可信区间,则可能得出相反的结论。贝叶斯建议使用可信区间来测试点零值,这是有误导性的,应该不予考虑。零假设值可能在可信区间之外,但受到贝叶斯因子的支持(类型I冲突),或者相反,零假设值可能在可信区间内,但不受贝叶斯因子的支持(类型II冲突)。在R中开发了两个计算机程序,它们证实存在可计数的无限数量的情况,其中贝叶斯可信区间与贝叶斯假设检验不兼容。
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来源期刊
CiteScore
0.50
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0.00%
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5
期刊介绍: The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.
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