Comparer des méthodes

	Validité nomologique	Modélisation par équations structurelles
Domaine	Psychométrie	Statistiques de recherche
Famille	Latent structure	Process / pipeline
Année d'origine	1955	1921
Auteur d'origine	Lee J. Cronbach & Paul E. Meehl	Sewall Wright
Type	Validity evidence framework	Method
Source fondatrice	Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302.	Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm.
Alias	nomological network validity, construct network validity, nomological web validity	SEM, path analysis, latent variable modeling, causal modeling
Apparentées	6	3
Résumé	Nomological validity evaluates whether a construct behaves as theory predicts within a broader network of related constructs. It is not a single statistical test but an accumulation of evidence that the measure fits coherently into a web of theoretically grounded relationships — demonstrating that what is measured is what the theory says it should measure.	Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis.