Using the potential outcome framework to estimate optimal sample size for cluster randomized trials: a simulation-based algorithm

DOI10.1080/00949655.2021.1946806OpenAlexW3184982906MaRDI QIDQ3390338

Roee Gutman, Ruoshui Zhai

Publication date: 24 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635296

zbMATH Keywords

sample size estimationcluster randomized trialspotential outcomes frameworkcausal estimand

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

CRTsampleSearch

Uses Software

• R
• Stata
• CRTSize

Cites Work

• Randomization Inference in a Group–Randomized Trial of Treatments for Depression
• Bayesian inference for causal effects: The role of randomization
• A paradox from randomization-based causal inference
• Sample Size Estimation in Cluster Randomized Studies with Varying Cluster Size
• Estimating Intraclass Correlation for Binary Data
• Regression Analysis of Count Data
• Causal Inference for Statistics, Social, and Biomedical Sciences
• Two classes of group divisible partial diallel crosses
• Sampling
• Design of observational studies

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