Compară metode

	Model Robust de Efecte Mixte Liniare	Testul de permutare (randomizare)
Domeniu	Statistică	Statistică
Familie	Regression model	Regression model
Anul apariției	2016	2005
Autorul original	Richardson & Welsh (robust REML); Koller (robustlmm implementation)	Good (2005); Edgington & Onghena (2007); resampling tradition
Tip	Robust linear mixed-effects model	Nonparametric resampling test
Sursa seminală	Koller, M. (2016). robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models. Journal of Statistical Software, 75(6), 1-24.	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Denumiri alternative	robust mixed-effects model, robust linear mixed model, robust LMM, Robust Karma Etkiler Modeli	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Înrudite	5	5
Rezumat	The robust mixed model is a linear mixed-effects model for panel and repeated-measures data that tolerates outliers and heavy-tailed errors. It replaces the usual likelihood with bounded-influence estimating equations, building on the robust restricted maximum likelihood of Richardson and Welsh (1995) and the robustlmm implementation of Koller (2016).	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.