方法对比
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| 贝叶斯多元方差分析 (Bayesian MANOVA)× | 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≠ | 1970s–2010s | 2009 (modern form); 1961 (Jeffreys prior framework) |
| 提出者≠ | Bayesian framework applied to MANOVA; foundational multivariate Bayesian work by Dickey (1974) and Rouder et al. (2012) | Harold Jeffreys (foundational); operationalized by Rouder et al. |
| 类型≠ | Bayesian multivariate group comparison | Bayesian hypothesis test |
| 开创性文献≠ | Olkin, I., & Rubin, H. (1964). Multivariate beta distributions and independence properties of the Wishart distribution. The Annals of Mathematical Statistics, 35(1), 261–269. 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 MANOVA, Bayesian multivariate ANOVA, BF-MANOVA, Bayesian multivariate group comparison | Bayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-test |
| 相关≠ | 5 | 3 |
| 摘要≠ | Bayesian Multivariate Analysis of Variance (Bayesian MANOVA) extends the classical MANOVA framework by replacing null-hypothesis significance testing with Bayesian inference. It uses prior distributions on multivariate group means and covariance structures, updates them with data to yield posterior distributions, and quantifies evidence through Bayes factors rather than p-values. | 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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