Participant-data integrity and harmonization

Reconcile participant variables across studies

Retain the original variable definitions and a versioned transformation dictionary. Resolve integrity queries with study teams; unmeasured variables cannot be recovered by relabeling columns.

Flow diagram

Participant-data integrity and harmonizationF1.S1Reconcile study dataF1.S2Check integrity and resolve queriesF1.S3Map variables and outcomesF1.S4Harmonize without erasingdifferencesF1.S5Freeze harmonized specificationsF1.N1Harmonization dictionaryStudy variableCommondefinitionTransformationMissingnessVerificationPredictorsOutcomesTime originFollow-upF1.N2Assumptions and rationaleF1.N3Method and protocol evidenceF1.S0 Start flowParticipant-data integrity andharmonizationF1.S999 End flowEnd flow

Steps

Reconcile study data

Check counts, allocation and follow-up against protocols and publications.

Check integrity and resolve queries

Define duplicate, range, chronology and source-query procedures.

Map variables and outcomes

Retain source definitions, units, instruments and time origins.

Harmonize without erasing differences

Record derivations, incompatible measures and missing fields by study.

Freeze harmonized specifications

Version mappings and reproducible transformations before analysis.

Participant-data integrity and harmonization

End flow

Tables and supporting information

Harmonization dictionary

Harmonization dictionaryStudy variableCommondefinitionTransformationMissingnessVerificationPredictorsOutcomesTime originFollow-up

Keep mappings and derivation metadata; do not upload identifiable records into this scaffold.

Assumptions and rationale

Harmonization must not silently equate different constructs or invent unobserved measurements.

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.

Sources