Researchers increasingly use Bayes factor for hypotheses evaluation. There are two main applications: null hypothesis Bayesian testing (NHBT) and informative hypothesis Bayesian testing (IHBT). As will be shown in this article, NHBT is sensitive to the specification of the scale parameter of the prior distribution, while IHBT is not. As will also be shown in this article, for NHBT using four different Bayes factors, use of the recommended default values for the scaling parameters results in unpredictable operating characteristics, that is, the Bayes factor will usually be biased against or in favor of the null hypothesis. As will furthermore be shown in this article, this problem can be addressed by choosing the scaling parameter such that the Bayes factor is 19 in favor of the null hypothesis over the alternative hypothesis if the observed effect size is equal to zero, because this renders a Bayes factor with clearly specified operating characteristics. However, this does not solve all problems regarding NHBT. The discussion of this article contains elaborations with respect to: the multiverse of Bayes factors; the choice of “19”; Bayes factor calibration outside the context of the univariate normal linear model; and, reporting the results of NHBT. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

中文翻译：

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零假设贝叶斯检验的先验敏感性。

研究人员越来越多地使用贝叶斯因子来评估假设。主要有两个应用：原假设贝叶斯检验（NHBT）和信息假设贝叶斯检验（IHBT）。如本文所示，NHBT 对先验分布的尺度参数的规范敏感，而 IHBT 则不然。正如本文中还将展示的那样，对于使用四种不同贝叶斯因子的 NHBT，使用推荐的缩放参数默认值会导致不可预测的操作特性，即贝叶斯因子通常会偏向或偏向于零假设。正如本文将进一步展示的那样，这个问题可以通过选择缩放参数来解决，如果观察到的效果大小等于零，贝叶斯因子为 19，支持零假设而不是替代假设，因为这会呈现具有明确指定操作特征的贝叶斯因子。然而，这并不能解决有关 NHBT 的所有问题。本文的讨论包含以下方面的详细说明：贝叶斯因子的多元宇宙；选择“19”；单变量正态线性模型上下文之外的贝叶斯因子校准；报告 NHBT 的结果。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）本文的讨论包含以下方面的详细说明：贝叶斯因子的多元宇宙；选择“19”；单变量正态线性模型上下文之外的贝叶斯因子校准；报告 NHBT 的结果。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）本文的讨论包含以下方面的详细说明：贝叶斯因子的多元宇宙；选择“19”；单变量正态线性模型上下文之外的贝叶斯因子校准；报告 NHBT 的结果。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）