Comparer des méthodes

	Recherche par tests de modèles sur données de panel	Analyse Factorielle Confirmatoire (AFC)
Domaine	Conception de la recherche	Psychométrie
Famille	Process / pipeline	Latent structure
Année d'origine	1970s–1980s (panel econometrics and SEM matured in parallel)	1969
Auteur d'origine	Developed across econometrics (Hsiao, Hausman) and psychometrics (Jöreskog, Bollen)	Karl Gustav Jöreskog
Type	Quantitative longitudinal research design	Hypothesis-testing latent variable model
Source fondatrice	Bollen, K. A. (1989). Structural Equations with Latent Variables. Wiley. ISBN: 978-0471011712	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	panel SEM, longitudinal model testing, panel structural equation modeling, panel-based hypothesis testing	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	4	4
Résumé	Panel-based model testing research combines the longitudinal power of panel survey designs with the confirmatory rigor of structural model testing — such as structural equation modeling (SEM), path analysis, or confirmatory factor analysis — applied to data collected from the same units (individuals, firms, countries) across multiple time points. This approach enables researchers to test theoretically specified causal and mediation structures while controlling for unobserved unit-level heterogeneity and examining how relationships unfold over time.	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.