Generate Synthetic Raw Demographics
Creates realistic dummy data for testing SDTM transformations and downstream programming without exposing patient information.
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CDISC Presentation · R/Jupyter
CDISC Implementation Experiences Using R
A notebook-based implementation pathway from synthetic raw demographics through an SDTM-compliant DM domain and subject-level ADSL dataset.
Workflow
A practical progression from source data to an analysis-ready subject dataset.
01Synthetic raw DM
→02SDTM DM
→03SDTM inputs
→04ADSL
Map Raw Demographics to SDTM DM
Transforms source variables into a compliant Demographics domain with standardized structure, attributes, dates, and controlled values.
Generate SDTM-Based Inputs for ADSL
Prepares mock SDTM source inputs required for subject-level ADaM derivations.
Generate ADSL
Builds the subject-level analysis dataset from the prepared inputs and documents the derivation flow.
Portfolio value
Standards knowledge demonstrated through executable implementation.
Standards translation
CDISC concepts are expressed as concrete transformations and dataset structures.
Synthetic-by-design
The workflow is suitable for public technical demonstration because it begins with generated data.
End-to-end continuity
The notebooks connect raw collection concepts to standardized tabulation and analysis datasets.
RJupyterCDISCSDTMADaMDMADSL
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