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How the Maximal Evidence of P-Values Against Point Null Hypotheses Depends on Sample Size

机译：针对点零假设的P值的最大证据如何取决于样本量

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摘要

Minimum Bayes factors are commonly used to transform two-sided p-values to lower bounds on the posterior probability of the null hypothesis. Several proposals exist in the literature, but none of them depends on the sample size. However, the evidence of a p-value against a point null hypothesis is known to depend on the sample size. In this article, we consider p-values in the linear model and propose new minimum Bayes factors that depend on sample size and converge to existing bounds as the sample size goes to infinity. It turns out that the maximal evidence of an exact two-sided p-value increases with decreasing sample size. The effect of adjusting minimum Bayes factors for sample size is shown in two applications.
机译：最小贝叶斯因子通常用于将两侧p值转换为原假设的后验概率的下限。文献中存在一些建议，但都不取决于样本量。但是，已知针对点零假设的p值证据取决于样本量。在本文中，我们考虑了线性模型中的p值，并提出了新的最小贝叶斯因子，该因子取决于样本大小，并随着样本大小达到无穷大而收敛到现有边界。结果表明，随着样本量的减少，确切的双向p值的最大证据也会增加。在两个应用程序中显示了为样本大小调整最小贝叶斯因子的效果。

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