方法对比
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| 贝叶斯威尔科克森符号秩检验× | 配对样本t检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 2014–2017 | 1908 |
| 提出者≠ | Benavoli, Corani, Mangili, and colleagues | Student (W. S. Gosset) |
| 类型≠ | Bayesian nonparametric paired test | Parametric mean comparison |
| 开创性文献≠ | 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 ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| 别名 | Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test | dependent t-test, matched pairs t-test, repeated measures t-test, within-subjects t-test |
| 相关≠ | 2 | 3 |
| 摘要≠ | 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. | The paired samples t-test is a parametric hypothesis test that compares the means of two related measurements from the same subjects or matched pairs to determine whether the average difference is significantly different from zero. It leverages the dependency between observations to produce a more powerful test than its independent-samples counterpart. |
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