方法对比
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| 贝叶斯 Mann-Whitney U 检验× | 贝叶斯威尔科克森符号秩检验× | |
|---|---|---|
| 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) | 2014–2017 |
| 提出者≠ | van Doorn, Ly, Marsman, Wagenmakers (building on Mann & Whitney 1947) | Benavoli, Corani, Mangili, and colleagues |
| 类型≠ | Bayesian nonparametric two-sample test | Bayesian nonparametric paired 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 ↗ | Benavoli, A., Corani, G., & Mangili, F. (2014). Should we really use post-hoc tests based on mean-ranks? Journal of Machine Learning Research, 17(5), 1–10. link ↗ |
| 别名≠ | Bayesian rank-sum test, Bayesian Wilcoxon rank-sum test, Bayesian nonparametric two-sample test | Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test |
| 相关≠ | 3 | 2 |
| 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 Wilcoxon signed-rank test is a Bayesian nonparametric method for comparing two paired or related samples. Rather than returning a single p-value, it produces posterior probabilities that one condition is better, practically equivalent, or worse than the other, enabling richer and more interpretable inference for paired continuous or ordinal data without assuming normality. |
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