Sammenlign metoder

	Robust nomologisk validitet	Strukturmodellering
Fagfelt	Psykometri	Forskningsstatistikk
Familie	Latent structure	Process / pipeline
Opprinnelsesår	1955	1921
Opphavsperson	Cronbach & Meehl (seminal framework); later extended by Shadish, Cook, and Campbell	Sewall Wright
Type	Validity assessment / construct validation	Method
Opprinnelig kilde	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, robust validity testing, nomological validity, RNV	SEM, path analysis, latent variable modeling, causal modeling
Relaterte	5	3
Sammendrag	Robust nomological validity evaluates whether a psychological construct relates to theoretically expected variables in the predicted directions, using statistically robust estimation methods that remain trustworthy when distributional assumptions are violated. It tests the construct's place within its nomological network — the web of theoretical relationships that define its meaning.	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.