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A Critical Evaluation of the FBST ev for Bayesian Hypothesis Testing

机译：FBST ev 用于贝叶斯假设检验的批判性评估

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Abstract The “Full Bayesian Significance Test e-value”, henceforth FBST ev, has received increasing attention across a range of disciplines including psychology. We show that the FBST ev leads to four problems: (1) the FBST ev cannot quantify evidence in favor of a null hypothesis and therefore also cannot discriminate “evidence of absence” from “absence of evidence”; (2) the FBST ev is susceptible to sampling to a foregone conclusion; (3) the FBST ev violates the principle of predictive irrelevance, such that it is affected by data that are equally likely to occur under the null hypothesis and the alternative hypothesis; (4) the FBST ev suffers from the Jeffreys-Lindley paradox in that it does not include a correction for selection. These problems also plague the frequentist p-value. We conclude that although the FBST ev may be an improvement over the p-value, it does not provide a reasonable measure of evidence against the null hypothesis.
机译：摘要“全贝叶斯显著性检验创造价值”,从此FBST电动车,已经收到了在一系列的越来越多的关注学科包括心理学。FBST ev导致四个问题:(1)FBST电动汽车不能量化的证据支持一个零假设,因此也不能歧视“没有证据”从“没有证据”;(2) FBST ev是容易受到抽样定局;预测原理,这样它同样可能影响数据发生在零假设下备择假设;在它Jeffreys-Lindley悖论不包括选择的校正。问题也困扰频率论的假定值。得出这样的结论:尽管FBST ev可能是一个改善假定值,它不提供一个合理的措施对零的证据假设。

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