Power and sample size requirements for GEE analyses of cluster randomized crossover trials

DOI10.1002/sim.7995zbMATH Open1545.62411MaRDI QIDQ6625668

Elizabeth L. Turner, Unnamed Author, Andrew B. Forbes, John S. Preisser

Publication date: 28 October 2024

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

zbMATH Keywords

crossoversandwich variance estimatorfinite-sample correctiongeneralized estimating equations (GEE)cluster randomized trialsmatrix-adjusted estimating equations (MAEEs)

Mathematics Subject Classification ID

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

Cites Work

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• 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
• Optimal allocation of clusters in cohort stepped wedge designs
• Sample Size Estimation in Cluster Randomized Studies with Varying Cluster Size
• Sample Size Considerations for GEE Analyses of Three-Level Cluster Randomized Trials
• Correlated Binary Regression with Covariates Specific to Each Binary Observation
• Methods for the Statistical Analysis of Binary Data in Split-Cluster Designs
• Deletion diagnostics for generalised estimating equations
• 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
• Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models
• Marginally Specified Logistic‐Normal Models for Longitudinal Binary Data
• A Generalized Estimating Equations Approach for Spatially Correlated Binary Data: Applications to the Analysis of Neuroimaging Data
• A Comparison of Two Bias‐Corrected Covariance Estimators for Generalized Estimating Equations

Related Items (8)

Designing multicenter individually randomized group treatment trials ⋮ Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure ⋮ Sample size considerations for matched-pair cluster randomization design with incomplete observations of binary outcomes ⋮ Finite-sample adjustments in variance estimators for clustered competing risks regression ⋮ The batched stepped wedge design: a design robust to delays in cluster recruitment ⋮ Design and analysis of cluster randomized trials with time-to-event outcomes under the additive hazards mixed model ⋮ Sample size requirements for detecting treatment effect heterogeneity in cluster randomized trials ⋮ Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations

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