Salīdzināt metodes

	Bayesiskā šķirības faktoru analīze (BCFA)	Beijesiana testēšana par mērījumu nemainīgumu
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	2007–2012	2013
Autors	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov	Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot
Tips	Bayesian latent variable model	Bayesian multigroup latent variable test
Pirmavots	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232	Van de Schoot, R., Kluytmans, A., Tummers, L., Lugtig, P., Hox, J., & Muthen, B. (2013). Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance. Frontiers in Psychology, 4, 770.
Citi nosaukumi	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA	Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance
Saistītās	4	6
Kopsavilkums	Bayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parameter uncertainty naturally.	Bayesian measurement invariance testing evaluates whether a scale's factor loadings and item intercepts are equivalent across groups, using a Bayesian framework that allows parameters to deviate from strict equality by a small, probabilistically specified amount rather than imposing an exact constraint.