validate_adam()
Generate a comprehensive ADaM validation workflow for a dataset.
Usage
validate_adam(
data,
dataset,
study_id=None,
check_population_flags=True,
check_bds_structure=True,
check_traceability=True,
label=None,
**kwargs
)Creates a Validate object with checks for:
- Required variables present and non-null
- Population flag values (Y/N only, no nulls in flag columns)
- BDS structure: PARAMCD, PARAM, AVAL consistency
- ADTTE: CNSR values (0 or 1), AVAL >= 0
- TRT01P/TRT01A consistency (non-null, single value per subject in ADSL)
- Traceability variable presence
Parameters
data: Any-
The DataFrame to validate (pandas or polars).
dataset: str-
ADaM dataset name (e.g.,
"ADSL","BDS","ADAE","ADTTE"). This is case-insensitive. study_id: str | None = None-
Optional study identifier for the validation label.
check_population_flags: bool = True-
If
True, validate population flag columns (Y/N values only). check_bds_structure: bool = True-
If
True, validate BDS-specific structure (PARAMCD/PARAM/AVAL). check_traceability: bool = True-
If
True, check that traceability variables are non-null when present. label: str | None = None-
Custom label for the Validate object.
**kwargs: Any- Additional keyword arguments passed to the Validate constructor.
Returns
Validate- A configured (but not yet interrogated) Validate object.