Comparer des méthodes

	Oméga de McDonald bayésien	Alpha de Cronbach bayésien
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1999 (omega); 2010s (Bayesian estimation)	2011 (Bayesian form); 1951 (classical alpha)
Auteur d'origine	R. P. McDonald (omega); Bayesian extension developed by Kelley, Pornprasertmanit, and others	Padilla & Zhang (Bayesian adaptation); Cronbach (classical alpha, 1951)
Type	Reliability / internal consistency estimation	Bayesian reliability estimation
Source fondatrice	Kelley, K. & Pornprasertmanit, S. (2016). Confidence intervals for population reliability coefficients: Evaluation of methods, recommendations, and software for composite measures. Psychological Methods, 21(1), 69–92.	Padilla, M. A., & Zhang, G. (2011). Estimating internal consistency using Bayesian methods. Journal of Modern Applied Statistical Methods, 10(1), 277–286.
Alias	Bayesian omega, Bayesian composite reliability, posterior omega, Bayesian omega total	Bayesian alpha, Bayesian internal consistency, Bayes-alpha, posterior alpha
Apparentées	3	2
Résumé	Bayesian McDonald's omega applies Bayesian statistical estimation to the omega reliability coefficient, yielding a full posterior distribution over omega rather than a single point estimate. This provides credible intervals and probabilistic uncertainty quantification for the reliability of a composite or scale score, making it especially useful for small samples and complex factor structures.	Bayesian Cronbach's alpha applies Bayesian inference to estimate the classical internal-consistency coefficient, yielding a full posterior distribution over alpha rather than a single point estimate. This allows researchers to quantify uncertainty with credible intervals and incorporate prior knowledge, making reliability assessment more informative — especially with small or skewed samples.