Power considerations for generalized estimating equations analyses of four‐level cluster randomized trials
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Publication:6068806
DOI10.1002/bimj.202100081zbMath1523.62230arXiv2108.11466OpenAlexW4200228376MaRDI QIDQ6068806
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Publication date: 15 December 2023
Published in: Biometrical Journal (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2108.11466
sample sizeeigenvaluescluster randomized trialsextended nested exchangeable correlationmatrix-adjusted estimating equations (MAEE)
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 Considerations for GEE Analyses of Three-Level Cluster Randomized Trials
- Models for Longitudinal Data: A Generalized Estimating Equation Approach
- Statistical Power and Sample Size Requirements for Three Level Hierarchical Cluster Randomized Trials
- Sample Size and Power Calculations for Periodontal and Other Studies with Clustered Samples Using the Method of Generalized Estimating Equations
- A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations
- A Note on the Efficiency of Sandwich Covariance Matrix Estimation
- Small Sample Correction for the Variance of GEE Estimators
- Improved standard error estimator for maintaining the validity of inference in cluster randomized trials with a small number of clusters
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