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	Analisi Robusta della Mediazione Moderata	Modellizzazione di Equazioni Strutturali
Campo	Statistica	Statistica per la ricerca
Famiglia	Latent structure	Process / pipeline
Anno di origine	2007–2013	1921
Ideatore	Hayes, A. F.; building on Preacher, Rucker & Hayes (2007) for moderated mediation and robust bootstrap inference	Sewall Wright
Tipo	Conditional indirect effect model with robust inference	Method
Fonte seminale	Hayes, A. F. (2022). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (3rd ed.). Guilford Press. ISBN: 978-1462549030	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.
Alias	robust conditional process analysis, robust mediated moderation, robust moderated indirect effects, robust conditional indirect effects	SEM, path analysis, latent variable modeling, causal modeling
Correlati	5	3
Sintesi	Robust moderated mediation tests whether the indirect effect of X on Y through a mediator M varies as a function of a moderator W, while using robust estimation (percentile or bias-corrected bootstrap, heteroscedasticity-consistent standard errors, or M-estimation) to protect inference against non-normality, outliers, and heteroscedasticity in the data.	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.