An Algorithmic Construction of All Unbiased Estimators of Variance Components in Linear Mixed Effects Models

• Activity Number: 341 - Random Effects and Mixed Models
• Type: Contributed
• Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Luyao Peng* and Subir Ghosh
• Companies: Univ. of California, Riverside and University of California, Riverside
• Keywords: Mixed Effects Model; Unbiased Estimation; Variance Components; MOM Estimator; Small Area Estimation; Minimizing Variance

Abstract

An algorithmic construction of all unbiased estimators of variance components in linear mixed effects models

Luyao Peng* and Subir Ghosh University of California, Riverside

The closed form expressions of all unbiased estimators of variance components in linear mixed effects models are presented. The method of moment (MOM) estimators are chosen as benchmarks for finding the unbiased estimators having smaller estimated variances than the corresponding MOM estimators. Examples are presented from small area estimation.

*Presenter