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| 베이즈 구성 타당도 평가× | 베이즈 측정 불변성 검정× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1955 / 2012 | 2013 |
| 창시자≠ | Cronbach & Meehl (validity framework); Muthén & Asparouhov (Bayesian SEM extension) | Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot |
| 유형≠ | Validity assessment / Bayesian inference | Bayesian multigroup latent variable test |
| 원전≠ | Muthén, B. & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335. DOI ↗ | 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. DOI ↗ |
| 별칭 | Bayesian validity analysis, Bayesian CFA-based validity, Bayesian structural validity, posterior construct validity | Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance |
| 관련 | 6 | 6 |
| 요약≠ | 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. | 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. |
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