Compară metode

	ANCOVA bayesiană	MANOVA Bayesiană
Domeniu	Statistică	Statistică
Familie	Hypothesis test	Hypothesis test
Anul apariției	2012 (formalized; Bayesian general linear models since 1960s)	1970s–2010s
Autorul original	Building on Jeffreys (1961) and developed formally for regression/ANCOVA by Rouder & Morey (2012)	Bayesian framework applied to MANOVA; foundational multivariate Bayesian work by Dickey (1974) and Rouder et al. (2012)
Tip	Bayesian parametric covariate-adjusted group comparison	Bayesian multivariate group comparison
Sursa seminală	Rouder, J. N., & Morey, R. D. (2012). Default Bayes factors for model selection in regression. Multivariate Behavioral Research, 47(6), 877–903.	Olkin, I., & Rubin, H. (1964). Multivariate beta distributions and independence properties of the Wishart distribution. The Annals of Mathematical Statistics, 35(1), 261–269.
Denumiri alternative	Bayesian ANCOVA, Bayesian analysis of covariance, B-ANCOVA, Bayesian covariate-adjusted group comparison	Bayesian MANOVA, Bayesian multivariate ANOVA, BF-MANOVA, Bayesian multivariate group comparison
Înrudite	5	5
Rezumat	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.	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.