Testing Hypotheses for Variance Components in Mixed Linear Models

DOI10.1080/02331889708802533zbMath0842.62059OpenAlexW2018174592MaRDI QIDQ4878157

Roman Zmyślony, Andrzej M. Michalski

Publication date: 4 August 1996

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889708802533

zbMATH Keywords

variance componentsblock designspowerscovariance matricesgroup of translationsmixed linear modelstwo-way classification modelsinvariance procedurelocally best quadratic unbiased estimator

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (15)

Unnamed Item ⋮ Simultaneous hypotheses testing in models with blocked compound symmetric covariance structure ⋮ Optimal estimation for doubly multivariate data in blocked compound symmetric covariance structure ⋮ Double tier cross nesting design models ⋮ F-tests with a rare pathology ⋮ On locally optimal invariant unbiased tests for the variance components ratio in mixed linear models ⋮ Jordan algebras, generating pivot variables and orthogonal normal models ⋮ Control of the truncation errors for generalizedFdistributions ⋮ Lattices of Jordan algebras ⋮ On testing variance components in unbalanced mixed linear model. ⋮ Generalized confidence intervals on the variance component in mixed linear models with two variance components ⋮ Ratio F test for testing simultaneous hypotheses in models with blocked compound symmetric covariance structure ⋮ Cross additivity in balanced cross nesting models ⋮ Inference for types and structured families of commutative orthogonal block structures ⋮ Considering the sample sizes as truncated Poisson random variables in mixed effects models

Cites Work

• Applying Wald's variance component test
• Optimum tests in unbalanced two-way models without interaction
• Tests Based on Admissible Estimators in Two Variance Components Models
• Computing the distribution of quadratic forms in normal variables
• Quadratic Subspaces and Completeness
• The Ratio of Variances in a Variance Components Model

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