Stepped-wedge cluster and participant selection
Define clusters and observation populations
Closed cohorts, open cohorts and repeated cross-sections have different observation processes. Keep unique people, repeated observations and cluster-period denominators distinct.
Flow diagram
Steps
Define cluster eligibility
Specify cluster boundaries, recruitment and consent.
Choose observation population
Select closed cohort, open cohort or repeated cross-sectional sampling with rationale.
Define within-period eligibility
Specify entry, replacement and repeated participation rules.
Document allocation-aware recruitment
Record whether recruiters know the transition sequence and control selection bias.
Track cluster and period denominators
Keep unique people, observations and clusters distinct.
Included clusters
Record clusters using the documented inclusion definition. This count is not a disjoint partition of the other count nodes.
Unique participants
Record people using the documented inclusion definition. This count is not a disjoint partition of the other count nodes.
Eligible observations
Record observations using the documented inclusion definition. This count is not a disjoint partition of the other count nodes.
Stepped-wedge cluster and participant selection
End flow
Tables and supporting information
Stepped-wedge sampling rules
Repeated observations cannot be added as if they were unique participants.
Assumptions and rationale
Closed cohorts and repeated cross-sections imply different dependence, attrition and estimands.
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.