Comparer des méthodes

	MANOVA Bayésienne	ANCOVA bayésienne
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1970s–2010s	2012 (formalized; Bayesian general linear models since 1960s)
Auteur d'origine	Bayesian framework applied to MANOVA; foundational multivariate Bayesian work by Dickey (1974) and Rouder et al. (2012)	Building on Jeffreys (1961) and developed formally for regression/ANCOVA by Rouder & Morey (2012)
Type	Bayesian multivariate group comparison	Bayesian parametric covariate-adjusted group comparison
Source fondatrice	Olkin, I., & Rubin, H. (1964). Multivariate beta distributions and independence properties of the Wishart distribution. The Annals of Mathematical Statistics, 35(1), 261–269.	Rouder, J. N., & Morey, R. D. (2012). Default Bayes factors for model selection in regression. Multivariate Behavioral Research, 47(6), 877–903.
Alias	Bayesian MANOVA, Bayesian multivariate ANOVA, BF-MANOVA, Bayesian multivariate group comparison	Bayesian ANCOVA, Bayesian analysis of covariance, B-ANCOVA, Bayesian covariate-adjusted group comparison
Apparentées	5	5
Résumé	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.	Bayesian Analysis of Covariance (Bayesian ANCOVA) extends classical ANCOVA by placing prior distributions on group effects and covariate slopes, then updating them with observed data to obtain posterior distributions and Bayes factors. It quantifies evidence for group differences on a continuous outcome after statistically adjusting for one or more continuous covariates, without relying on p-value thresholds.