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Ceļu analīze×Modelēšana ar strukturālām vienādojumiem×
NozareStatistikaPētniecības statistika
SaimeLatent structureProcess / pipeline
Izcelsmes gads19211921
AutorsSewall WrightSewall Wright
TipsCausal / mediation modelMethod
PirmavotsWright, 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 ↗
Citi nosaukumiPA, path coefficient analysis, observed-variable SEM, causal path modelingSEM, path analysis, latent variable modeling, causal modeling
Saistītās53
KopsavilkumsPath 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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ScholarGateSalīdzināt metodes: Path Analysis · Structural Equation Modeling. Izgūts 2026-06-15 no https://scholargate.app/lv/compare