Salīdzināt metodes

	Robustas nomoloģiskās pamatotības pārbaude	Modelēšana ar strukturālām vienādojumiem
Nozare	Psihometrija	Pētniecības statistika
Saime	Latent structure	Process / pipeline
Izcelsmes gads	1955	1921
Autors	Cronbach & Meehl (seminal framework); later extended by Shadish, Cook, and Campbell	Sewall Wright
Tips	Validity assessment / construct validation	Method
Pirmavots	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.
Citi nosaukumi	nomological network validity, robust validity testing, nomological validity, RNV	SEM, path analysis, latent variable modeling, causal modeling
Saistītās	5	3
Kopsavilkums	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.