方法证据记录
Bayesian MANOVA
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.
源记录
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Bayesian Multivariate Analysis of Variance
分类方法记录 · hypothesis-test / statistics
- 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 10.1214/aoms/1177703748
- Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374. · DOI 10.1016/j.jmp.2012.08.001
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