Sample size calculation in three-level cluster randomized trials using generalized estimating equation models
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Publication:6627623
DOI10.1002/SIM.8670zbMATH Open1546.62475MaRDI QIDQ6627623
Jingxia Liu, Graham A. Colditz
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
relative efficiencygeneralized estimating equationcluster randomized trialnested correlation structurebias-corrected sandwich estimator
Cites Work
- Longitudinal data analysis using generalized linear models
- A Covariance Estimator for GEE with Improved Small‐Sample Properties
- Small-Sample Adjustments for Wald-Type Tests Using Sandwich Estimators
- Sample size estimation in cluster randomized studies with varying cluster size
- Sample Size Considerations for GEE Analyses of Three-Level Cluster Randomized Trials
- Analysis of Longitudinal Multiple-Source Binary Data Using Generalized Estimating Equations
- Repeated measurement analysis for nonnormal data in small samples
- Statistical Power and Sample Size Requirements for Three Level Hierarchical Cluster Randomized Trials
- Sample Size Calculations for Studies with Correlated Observations
- Sample Size and Power Calculations for Periodontal and Other Studies with Clustered Samples Using the Method of Generalized Estimating Equations
- A Note on the Efficiency of Sandwich Covariance Matrix Estimation
- Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models
- Small sample characteristics of generalized estimating equations
- Small Sample Correction for the Variance of GEE Estimators
- A Comparison of Two Bias‐Corrected Covariance Estimators for Generalized Estimating Equations
- Optimal designs in three-level cluster randomized trials with a binary outcome
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