Compara mètodes

	Errors estàndard robustes a clústers	Test de permutació (aleatorització)
Camp	Estadística	Estadística
Família	Regression model	Regression model
Any d'origen	1986	2005
Autor original	Liang & Zeger (GEE sandwich); Cameron & Miller (practitioner synthesis)	Good (2005); Edgington & Onghena (2007); resampling tradition
Tipus	Robust variance estimation for regression	Nonparametric resampling test
Font seminal	Liang, K. Y. & Zeger, S. L. (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73(1), 13-22.	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Àlies	clustered standard errors, cluster-robust inference, clustered variance estimator, Küme Robust Standart Hatalar	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Relacionats	4	5
Resum	Cluster-robust standard errors correct the variance of regression coefficients when observations are correlated within clusters such as schools, hospitals, or regions. The clustered sandwich estimator grew out of Liang & Zeger's (1986) generalized estimating equations and was synthesized for applied work by Cameron & Miller (2015), delivering valid inference when ordinary standard errors would be too small.	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.