Studies on the estimation of the slope parameter in the simple linear regression model with one-fold nested error structure

DOI10.1080/03610918908812754zbMath0695.62159OpenAlexW2004900030MaRDI QIDQ3471501

Lee-Ing Tong, Paul L. Cornelius

Publication date: 1989

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

Full work available at URL: https://doi.org/10.1080/03610918908812754

zbMATH Keywords

mean squared errorMonte Carlo simulationmaximum likelihoodgeneralized least squaresmixed modelshierarchical classificationsimple linear regressiontwo-stage samples

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items (3)

Maximum likelihood estimation in simple linear regression with one fold nested error ⋮ Minimum Variance Quadratic Unbiased Estimation for the Variance Components in Simple Linear Regression with Onefold Nested Error ⋮ Studies on the hypothesis testing of the slope parameter in the simple linear regression model with one-fold nested error structure

Cites Work

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• Approximations for Standard Errors of Estimators of Fixed and Random Effect in Mixed Linear Models
• Unbiasedness of two-stage estimation and prediction procedures for mixed linear models
• Restricted Maximum Likelihood (REML) Estimation of Variance Components in the Mixed Model

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