Estimating Variance Components and Random Effects Using the Box-Cox Transformation in the Linear Mixed Model

DOI10.1080/03610920903411192zbMath1208.62109OpenAlexW2012209659MaRDI QIDQ3083800

Matthew J. Gurka, Lloyd J. Edwards

Publication date: 23 March 2011

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920903411192

zbMATH Keywords

normalitylongitudinal data

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Analysis of variance and covariance (ANOVA) (62J10)

Cites Work

• Unnamed Item
• Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data
• Random-Effects Models for Longitudinal Data
• Testing transformations for the linear mixed model
• The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data
• A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
• Smearing Estimate: A Nonparametric Retransformation Method
• The Analysis of Transformed Data
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• An Analysis of Transformations Revisited
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• A Monte Carlo Investigation of the Box-Cox Transformation in Small Samples
• Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood
• Mixed Models
• Linear mixed models for longitudinal data

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