Vertaile menetelmiä

	Robustin moderointianalyysi	Robustipolkuanalyysi
Tieteenala	Tilastotiede	Tilastotiede
Menetelmäperhe	Latent structure	Latent structure
Syntyvuosi	2007	1998
Kehittäjä	Hayes & Cai; Wilcox	Yuan & Bentler (robust SEM/path framework); Huber (M-estimation foundation)
Tyyppi	Robust regression-based interaction test	Causal path modeling with robust estimation
Alkuperäislähde	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.	Yuan, K.-H. & Bentler, P. M. (1998). Robust mean and covariance structure analysis. British Journal of Mathematical and Statistical Psychology, 51(1), 63–88.
Rinnakkaisnimet	robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing	robust PA, path analysis with robust standard errors, robust causal path modeling, robust structural path modeling
Liittyvät	5	6
Tiivistelmä	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 path analysis applies robust estimation — such as sandwich standard errors or M-estimation — to path models that specify directed causal relationships among observed variables. It preserves valid inference about path coefficients and indirect effects when data violate normality, contain outliers, or exhibit heteroscedasticity that would distort conventional standard errors.