Improving Predictions When Interest Focuses on Extreme Random Effects

DOI10.1080/01621459.2021.1938583zbMath1514.62250OpenAlexW3170354772MaRDI QIDQ6107225

John M. Neuhaus, Charles E. McCulloch

Publication date: 3 July 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2021.1938583

zbMATH Keywords

best linear unbiased predictionprofilingmean squared error of prediction

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Statistics of extreme values; tail inference (62G32)

Cites Work

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• Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data
• Statistical and clinical aspects of hospital outcomes profiling
• The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data
• Log‐gamma linear‐mixed effects models for multiple outcomes with application to a longitudinal glaucoma study
• Mixture Models, Outliers, and the EM Algorithm
• Efficient Estimation for Patient‐Specific Rates of Disease Progression Using Nonnormal Linear Mixed Models
• The Identification of “Unusual” Health-Care Providers From a Hierarchical Model

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