We describe Bayes factors functions based on the sampling distributions of \emph{z}, \emph{t}, $χ^2$, and \emph{F} statistics, using a class of inverse-moment prior distributions to define alternative hypotheses. These non-local alternative prior distributions are centered on standardized effects, which serve as indices for the Bayes factor function. We compare the conclusions drawn from resulting Bayes factor functions to those drawn from Bayes factors defined using local alternative prior specifications and examine their frequentist operating characteristics. Finally, an application of Bayes factor functions to replicated experimental designs in psychology is provided.

翻译：本文基于\emph{z}统计量、\emph{t}统计量、$χ^2$统计量及\emph{F}统计量的抽样分布，描述了一类贝叶斯因子函数，其中采用一类逆矩先验分布来定义备择假设。这些非局部备择先验分布以标准化效应为中心，后者作为贝叶斯因子函数的指标。我们将由此得到的贝叶斯因子函数所得结论，与采用局部备择先验设定所定义的贝叶斯因子所得结论进行比较，并考察其频率学派操作特性。最后，提供了贝叶斯因子函数在心理学重复实验设计中的应用实例。