The Use of Permutation Tests for Variance Components in Linear Mixed Models

DOI10.1080/03610926.2011.587933zbMath1296.62103OpenAlexW2090673225MaRDI QIDQ3167839

Carla Rampichini, Leonardo Grilli, Monjed Hisham Samuh, Luigi Salmaso, Nicola Lunardon

Publication date: 29 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.587933

zbMATH Keywords

likelihood ratio testpermutation testlinear mixed modelbootstrap testvariance component

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Generalized linear models (logistic models) (62J12) Nonparametric statistical resampling methods (62G09)

Related Items (6)

Testing the absence of random effects in the nested-error regression model using orthogonal transformations ⋮ Permutation confidence region for multiple regression and fidelity to asymptotic approximation ⋮ Asymptotic distribution of likelihood ratio test statistics for variance components in nonlinear mixed effects models ⋮ Permutation inference distribution for linear regression and related models ⋮ Testing random effects in linear mixed models: another look at the F‐test (with discussion) ⋮ A note on covariance decomposition in linear models with nested-error structure: new and alternative derivations of the \(F\)-test

Uses Software

• faraway
• RLRsim

Cites Work

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• The Use of Score Tests for Inference on Variance Components
• Likelihood Ratio Tests in Linear Mixed Models with One Variance Component
• Likelihood Ratio Testing of Variance Components in the Linear Mixed-Effects Model Using Restricted Maximum Likelihood
• An Application of Multilevel Model Prediction to NELS:88
• Variance Components Testing in the Longitudinal Mixed Effects Model
• Bootstrap tests for variance components in generalized linear mixed models
• A Note on Permutation Tests for Variance Components in Multilevel Generalized Linear Mixed Models
• Testing Statistical Hypotheses
• Efficient Inference in a Random Coefficient Regression Model
• Linear mixed models for longitudinal data

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