Cluster sample size and testing
Specify correlation sizes and power
Include cluster count, size distribution, intracluster correlation and cluster loss in scenarios. The equal-size design-effect expression is illustrative, not a general substitute for a design-specific calculation.
Flow diagram
Steps
Define design and primary contrast
Specify number of clusters, allocation and target estimand.
Specify within-cluster correlation
Record ICC evidence, outcome variation and plausible uncertainty.
Model unequal cluster sizes
Include expected size distribution, imbalance and informative-size concerns.
Account for dropout and small samples
Separate cluster loss from participant attrition and justify inferential methods.
Document power scenarios
Use a design-compatible formula or simulation with assumptions and provenance.
Cluster sample size and testing
End flow
Tables and supporting information
Cluster design scenarios
No numerical default is supplied; include number of clusters as well as total people.
Equal-size cluster design effect
The simple design effect assumes equal cluster size and exchangeable correlation; it is not a universal cluster-trial power calculation.
Method and protocol evidence
Attach the protocol, methodological sources and versioned software specification supporting these decisions. Record citations and provenance; do not enter participant identifiers.