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Compară metode

Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Cercetare robustă de testare a modelelor×Cercetarea de Testare a Modelului×
DomeniuDesign de cercetareDesign de cercetare
FamilieProcess / pipelineProcess / pipeline
Anul apariției1988–19981970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s
Autorul originalAlbert Satorra & Peter M. Bentler; Ke-Hai YuanKarl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition
TipQuantitative model-testing research design with robust estimationConfirmatory quantitative research design
Sursa seminalăSatorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link ↗Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344
Denumiri alternativerobust SEM, robust structural model testing, robust fit evaluation, robust model evaluation researchmodel-based research, structural model testing, theory-testing research, MTR
Înrudite65
RezumatRobust model testing research applies structural or path models to data while explicitly accounting for violations of multivariate normality and other distributional assumptions. Rather than discarding non-normal data or forcing transformations, it uses corrected estimators — most notably the Satorra-Bentler scaled chi-square and Yuan-Bentler robust standard errors — to produce trustworthy fit indices and parameter estimates even when classical maximum likelihood assumptions are breached.Model testing research is a confirmatory quantitative design in which the researcher specifies a theoretical model — depicting hypothesized relationships among constructs — and then tests how well that model fits empirical data. Drawing primarily on structural equation modeling (SEM) and confirmatory factor analysis (CFA), it evaluates whether the data-implied covariance structure is consistent with the theoretically derived one, yielding fit indices that indicate model-data correspondence.
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  3. PUBLISHED

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ScholarGateCompară metode: Robust Model Testing Research · Model Testing Research. Preluat la 2026-06-15 de pe https://scholargate.app/ro/compare