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	Analisi di Moderazione Robusta	Modellazione di Equazioni Strutturali Robusta
Campo	Statistica	Statistica
Famiglia	Latent structure	Latent structure
Anno di origine	2007	1994
Ideatore	Hayes & Cai; Wilcox	Albert Satorra & Peter M. Bentler
Tipo	Robust regression-based interaction test	Latent variable / path model with robust inference
Fonte seminale	Hayes, A. F. & Cai, L. (2007). Using heteroscedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behavior Research Methods, 39(4), 709–722.	Satorra, 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 (pp. 399–419). Sage.
Alias	robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing	Robust SEM, SEM with robust standard errors, Satorra-Bentler SEM, non-normal SEM
Correlati	5	5
Sintesi	Robust moderation analysis tests whether the effect of a predictor on an outcome depends on the level of a moderator variable, using estimation methods that remain valid under non-normality, heteroscedasticity, or the presence of influential outliers. It is the preferred approach when standard ordinary least squares assumptions cannot be trusted.	Robust structural equation modeling (Robust SEM) applies the full SEM framework — simultaneous estimation of measurement and structural relations among latent variables — while using corrected test statistics and sandwich standard errors that remain valid when observed data depart from multivariate normality. The Satorra-Bentler scaled chi-square is the most widely used correction.