Klauer Karl Christoph, Meyer-Grant Constantin G, Kellen David
Department of Psychology, Albert-Ludwigs-Universität Freiburg, 79085, Freiburg, Germany.
Department of Psychology, Syracuse University, Syracuse, NY, USA.
Psychon Bull Rev. 2025 Jun;32(3):1070-1094. doi: 10.3758/s13423-024-02612-2. Epub 2024 Nov 25.
We develop alternative families of Bayes factors for use in hypothesis tests as alternatives to the popular default Bayes factors. The alternative Bayes factors are derived for the statistical analyses most commonly used in psychological research - one-sample and two-sample t tests, regression, and ANOVA analyses. They possess the same desirable theoretical and practical properties as the default Bayes factors and satisfy additional theoretical desiderata while mitigating against two features of the default priors that we consider implausible. They can be conveniently computed via an R package that we provide. Furthermore, hypothesis tests based on Bayes factors and those based on significance tests are juxtaposed. This discussion leads to the insight that default Bayes factors as well as the alternative Bayes factors are equivalent to test-statistic-based Bayes factors as proposed by Johnson. Journal of the Royal Statistical Society Series B: Statistical Methodology, 67, 689-701. (2005). We highlight test-statistic-based Bayes factors as a general approach to Bayes-factor computation that is applicable to many hypothesis-testing problems for which an effect-size measure has been proposed and for which test power can be computed.
我们开发了替代的贝叶斯因子族，用于假设检验，作为流行的默认贝叶斯因子的替代方案。这些替代贝叶斯因子是为心理学研究中最常用的统计分析而推导出来的——单样本和两样本t检验、回归分析和方差分析。它们具有与默认贝叶斯因子相同的理想理论和实践特性，满足额外的理论要求，同时减轻了我们认为不合理的默认先验的两个特征。它们可以通过我们提供的R包方便地计算出来。此外，还将基于贝叶斯因子的假设检验与基于显著性检验的假设检验并列。这一讨论得出的见解是，默认贝叶斯因子以及替代贝叶斯因子等同于约翰逊提出的基于检验统计量的贝叶斯因子。《皇家统计学会会刊B辑：统计方法》，67卷，689 - 701页。（2005年）。我们强调基于检验统计量的贝叶斯因子是一种通用的贝叶斯因子计算方法，适用于许多已经提出效应量度量且可以计算检验功效的假设检验问题。
