Sampling and analysis plan
Account for matching and sampling
An odds ratio is not automatically a risk ratio. Interpret it in light of control sampling and distinguish unmatched summaries from conditional analyses of matched sets. Sparse or uninformative matched sets affect precision.
Flow diagram
Steps
Specify the sampling design
Document cumulative, density or other control-sampling scheme.
Define the estimand and interpretation
State how control sampling determines interpretation. Cumulative sampling estimates an odds ratio (a risk-ratio approximation needs a rare outcome); incidence-density sampling can estimate a rate ratio without that approximation.
Choose analysis for matching and sampling
Specify conditional/unconditional methods and matching-variable handling.
Assess information and precision
Justify sample information, discordant sets and uncertainty.
Specify missingness and model checks
Plan diagnostics and sensitivity to matching and exposure definitions.
Sampling and analysis plan
End flow
Tables and supporting information
Case-control analysis plan
Do not automatically relabel odds ratios as risk ratios.
Effect interpretation
Effect interpretation depends on the control-sampling scheme and study assumptions; justify any approximation.
Unmatched exposure odds ratio
a and b are exposed and unexposed cases; c and d are exposed and unexposed controls. This is an unadjusted two-by-two summary. Matched designs require an analysis that respects matched sets. With cumulative sampling, the outcome odds ratio approximates a risk ratio only under a rare-outcome condition; incidence-density sampling supports a rate-ratio interpretation under its sampling assumptions.