Linganisha mbinu

	Tathmini ya Uhakiki wa Ujenzi wa Kibayesiani	Uchanganuzi wa Kimfumo wa Uhakiki (CFA)
Nyanja	Saikometriki	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	1955 / 2012	1969
Mwanzilishi	Cronbach & Meehl (validity framework); Muthén & Asparouhov (Bayesian SEM extension)	Karl Gustav Jöreskog
Aina	Validity assessment / Bayesian inference	Hypothesis-testing latent variable model
Chanzo asilia	Muthén, B. & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Majina mbadala	Bayesian validity analysis, Bayesian CFA-based validity, Bayesian structural validity, posterior construct validity	CFA, confirmatory FA, measurement model, restricted factor analysis
Zinazohusiana	6	4
Muhtasari	Bayesian construct validity assessment uses Bayesian confirmatory factor analysis and related Bayesian structural equation models to evaluate whether a scale or test measures the intended latent construct. It yields full posterior distributions for factor loadings, structural coefficients, and model-fit indices rather than single point estimates, enabling more nuanced and uncertainty-aware validity conclusions.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.