On Bayes Factor Functions

doi:10.1214/25-BA1562

2025-12-01

PRE

DOI：10.1214/25-BA1562

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贝叶斯因子函数（BFFs）将贝叶斯因子表示为先验超参数的函数（Johnson et al., 2023; Datta et al., 2025a）。尽管早期研究主要关注正态-矩和伽马先验，但我们在Wagenmakers和Grasman（2025）近期研究的基础上，探索了用于构建BFFs的更广泛先验类。对于基于常见检验统计量的检验，我们的研究发现，逆矩和逆伽马先验在支持真实零假设和真实备择假设时，能够比其他默认先验产生更高的后验概率期望值。利用重复实验的检验统计量，我们还展示了矩法估计量如何指导这些家族中的先验参数选择，从而增强重复研究及元分析中的推断。

Keyword:

Bayes factor based on test statistic

meta-analysis

non-local prior density

inverse moment prior density

期刊

Bayesian Analysis

IF:

2.5

论文数:

被引数:

3.0K

机构

Texas A&M University System

学者数:

4.4W

论文数: 4.0W

被引数: 4.0K

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