Testing the absence of random effects in the nested-error regression model using orthogonal transformations

DOI10.1080/03610918.2019.1700278OpenAlexW2995000687WikidataQ126528688 ScholiaQ126528688MaRDI QIDQ5083016

Yahia S. El-Horbaty

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1700278

zbMATH Keywords

exchangeabilityvariance componentspermutation testexact testsorthogonal transformationscluster correlated data

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03)

Related Items

A note on covariance decomposition in linear models with nested-error structure: new and alternative derivations of the \(F\)-test

Uses Software

• R
• AS 155

Cites Work

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• Permutation Tests for Random Effects in Linear Mixed Models
• Random-Effects Models for Longitudinal Data
• New important developments in small area estimation
• \(U\)-tests for variance components in linear mixed models
• Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models
• A simple test for random effects in regression models
• The Use of Permutation Tests for Variance Components in Linear Mixed Models
• Algorithm AS 155: The Distribution of a Linear Combination of χ 2 Random Variables
• Transformations which preserve exchangeability and application to permutation tests
• Likelihood Ratio Tests in Linear Mixed Models with One Variance Component
• On testing random effects in the nested-error regression model
• Model Selection by Testing for the Presence of Small-Area Effects, and Application to Area-Level Data
• A Note on Permutation Tests for Variance Components in Multilevel Generalized Linear Mixed Models
• Testing for additivity in non‐parametric regression