方法对比
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| 贝叶斯 Mann-Whitney U 检验× | 贝叶斯独立样本t检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 2020 (Bayesian formulation); 1947 (classical test) | 2009 (modern form); 1961 (Jeffreys prior framework) |
| 提出者≠ | van Doorn, Ly, Marsman, Wagenmakers (building on Mann & Whitney 1947) | Harold Jeffreys (foundational); operationalized by Rouder et al. |
| 类型≠ | Bayesian nonparametric two-sample test | Bayesian hypothesis test |
| 开创性文献≠ | van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's rho. Journal of Applied Statistics, 47(16), 2984–3006. DOI ↗ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ |
| 别名≠ | Bayesian rank-sum test, Bayesian Wilcoxon rank-sum test, Bayesian nonparametric two-sample test | Bayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-test |
| 相关 | 3 | 3 |
| 摘要≠ | The Bayesian Mann-Whitney U test is a nonparametric Bayesian procedure for comparing two independent groups when data are ordinal or non-normal continuous. Instead of a binary reject/fail-to-reject decision, it quantifies the relative evidence for the null and alternative hypotheses through a Bayes factor, allowing researchers to conclude in favour of either hypothesis or express uncertainty. | The Bayesian independent samples t-test quantifies evidence for or against a mean difference between two independent groups using a Bayes factor rather than a p-value. Rooted in Jeffreys's probability framework and popularized by Rouder et al. (2009), it places a Cauchy prior on the standardized effect size and returns continuous evidence for both the null and alternative hypotheses. |
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