Performance of mixed effects models and generalized estimating equations for continuous outcomes in partially clustered trials including both independent and paired data

DOI10.1002/sim.10201MaRDI QIDQ6663832

Lisa N. Yelland, Jessica Kasza, Kylie M. Lange, Thomas R. Sullivan

Publication date: 15 January 2025

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

powerclinical trialssimulation studygeneralized estimating equationsmixed effects modelspartial clustering

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Marginal Analyses of Clustered Data When Cluster Size Is Informative
• Efficiency of Regression Estimates for Clustered Data
• Generalized Estimating Equations in Controlled Clinical Trials: Hypotheses Testing
• Equivalence of conditional and marginal regression models for clustered and longitudinal data
• Designing multicenter individually randomized group treatment trials
• Using simulation studies to evaluate statistical methods
• Sample size for partially nested designs and other nested or crossed designs with a continuous outcome when adjusted for baseline
• Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations

This page was built for publication: Performance of mixed effects models and generalized estimating equations for continuous outcomes in partially clustered trials including both independent and paired data