方法对比

	纵向普遍性理论	验证性因子分析（CFA）
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	1990s–2000s	1969
提出者	Webb, Shavelson, and colleagues, building on Cronbach et al. (1963) G-theory foundations	Karl Gustav Jöreskog
类型	Variance components / reliability estimation	Hypothesis-testing latent variable model
开创性文献	Webb, N. M., Shavelson, R. J., & Harrigan, E. H. (2007). Generalizability theory: Overview. In C. R. Rao & S. Sinharay (Eds.), Handbook of Statistics, Vol. 26: Psychometrics (pp. 1–43). Elsevier.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
别名	longitudinal G-theory, longitudinal GT, repeated-measures generalizability theory, G-theory for longitudinal designs	CFA, confirmatory FA, measurement model, restricted factor analysis
相关	4	4
摘要	Longitudinal generalizability theory extends classical G-theory to repeated-measures and longitudinal designs, decomposing score variance across persons, measurement occasions, raters, and items simultaneously. It quantifies how reliably scores can be generalized across time points, evaluators, and conditions — information that is invisible to cross-sectional reliability indices.	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.