Bandingkan kaedah

	Ujian Keterakalaan Pengukuran Bayesian	Analisis Faktor Konfirmatori Multi-Kumpulan (MG-CFA)
Bidang	Psikometrik	Psikometrik
Keluarga	Latent structure	Latent structure
Tahun asal	2013	1971
Pengasas	Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot	Karl Jöreskog
Jenis	Bayesian multigroup latent variable test	Measurement model / invariance test
Sumber perintis	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.	Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70.
Alias	Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Berkaitan	6	6
Ringkasan	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.	Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified.