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Stianalyse×Strukturel Ligningsmodellering×
FagområdeStatistikForskningsstatistik
FamilieLatent structureProcess / pipeline
Oprindelsesår19211921
OphavspersonSewall WrightSewall Wright
TypeCausal / mediation modelMethod
Oprindelig kildeWright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585. link ↗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. link ↗
AliasserPA, path coefficient analysis, observed-variable SEM, causal path modelingSEM, path analysis, latent variable modeling, causal modeling
Relaterede53
ResuméPath analysis tests a researcher-specified causal diagram among observed variables by decomposing their intercorrelations into direct effects, indirect (mediated) effects, and spurious associations. Developed by Sewall Wright in 1921, it is the observed-variable special case of structural equation modeling and remains a standard tool for theory-driven multivariate causal inference.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.
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ScholarGateSammenlign metoder: Path Analysis · Structural Equation Modeling. Hentet 2026-06-15 fra https://scholargate.app/da/compare