Salīdzināt metodes

	Bejeziešu ANKOVA (Bayesian ANCOVA)	Bayesiešu Vienpusējā ANOVA
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	2012 (formalized; Bayesian general linear models since 1960s)	1961 (foundations); 2012 (ANOVA Bayes factors)
Autors	Building on Jeffreys (1961) and developed formally for regression/ANCOVA by Rouder & Morey (2012)	Harold Jeffreys (foundations); Jeffrey Rouder et al. (default priors for ANOVA)
Tips	Bayesian parametric covariate-adjusted group comparison	Bayesian hypothesis test
Pirmavots	Rouder, J. N., & Morey, R. D. (2012). Default Bayes factors for model selection in regression. Multivariate Behavioral Research, 47(6), 877–903.	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.
Citi nosaukumi	Bayesian ANCOVA, Bayesian analysis of covariance, B-ANCOVA, Bayesian covariate-adjusted group comparison	Bayesian ANOVA, BF ANOVA, Bayes factor one-way ANOVA, Bayesian F-test
Saistītās	5	3
Kopsavilkums	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 one-way ANOVA tests whether the means of three or more independent groups differ by computing a Bayes factor — a ratio that quantifies how much more likely the data are under a model that allows group differences than under the null model that assumes equal means. Unlike the classical F-test, it provides direct evidence for or against the null hypothesis rather than merely rejecting or retaining it.