Estimation of variance components in normal linear mixed models with additivity

2015 ◽  
Author(s):  
Dário Ferreira ◽  
Sandra S. Ferreira ◽  
Célia Nunes ◽  
João T. Mexia
Keyword(s):  
Mixed Models ◽  
Variance Components ◽  
Linear Mixed Models ◽  
Estimation Of Variance

scholarly journals REHE: Fast Variance Components Estimation for Linear Mixed Models

2021 ◽  
Author(s):  
Kun Yue ◽  
Jing Ma ◽  
Timothy Thornton ◽  
Ali Shojaie
Keyword(s):  
Mixed Models ◽  
Variance Components ◽  
Linear Mixed Models ◽  
Real Data ◽  
Small Samples ◽  
Simulation Studies ◽  
Genetic Studies ◽  
Variance Components Estimation ◽  
Comparable Accuracy ◽  
Estimation Of Variance

AbstractLinear mixed models are widely used in ecological and biological applications, especially in genetic studies. Reliable estimation of variance components is crucial for using linear mixed models. However, standard methods, such as the restricted maximum likelihood (REML), are computationally inefficient and may be unstable with small samples. Other commonly used methods, such as the Haseman-Elston (HE) regression, may yield negative estimates of variances. Utilizing regularized estimation strategies, we propose the restricted Haseman-Elston (REHE) regression and REHE with resampling (reREHE) estimators, along with an inference framework for REHE, as fast and robust alternatives that provide non-negative estimates with comparable accuracy to REML. The merits of REHE are illustrated using real data and benchmark simulation studies.

U-tests for variance components in linear mixed models

Test ◽  
2013 ◽  
Vol 22 (4) ◽  
pp. 580-605 ◽  
Author(s):  
Juvêncio S. Nobre ◽  
Julio M. Singer ◽  
Pranab K. Sen
Keyword(s):  
Mixed Models ◽  
Variance Components ◽  
Linear Mixed Models
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