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Summary
EditUnder reviewWhat this benchmark meansREADME.mdPublic entries: Python and R. Passing coverage requires an installed inventory.
Goal: build one record per subject from the subject's exposure records,
with the subject's planned arm in ARM and the total dose administered in
TOTDOSE.
Input: exposure records, one per administration, carrying the site
(SITEID) and the dose given (EXDOSE), and a randomization list giving each
subject's planned arm (ARM) by site and subject.
Variables:
ARMwould be the subject's planned arm from the randomization list, and blank when the list has no record for the subject at that site.TOTDOSEwould be the sum of the doses of the subject's administrations.
Note: each subject's record summarizes all of the subject's administrations, and the randomization record is matched on an administration's site. The subject's record holds only the study and the subject, so it has no site to match on, and the run is rejected before any data is read and no artifact is accepted.
How to fix
A subject is enrolled at one site, so add the site to the record's grouping. It does not split any subject's record, and the record then holds the site to match on:
rows:
- id: subject
dataset: EX
group_by: [EX.STUDYID, EX.SITEID, EX.USUBJID]
When the randomization list identifies subjects without their site, match on the subject alone instead.
Expected failure
Editthe run is rejected; no artifact is acceptedexpected/error.yaml- phase
- validation
- condition
- ungrouped_driver_field
- rule
- ROW-5
expected/error.yaml
phase: validation
condition: ungrouped_driver_field
spec_paths:
- intermediates.RANDOMIZED.key
rule: ROW-5
context:
identifier: EX.SITEID
intermediate: RANDOMIZED
row: subject
dataset: EX
Inputs
Under review2 source filesUnexpected Output
Under reviewNo artifact is producedNo fixture files in this directory.
Human review and assessment
| Dataset Name | Variable Name | Variable Label | Type | Codelist/Controlled Terms | Core | Computational Method | Origin |
|---|---|---|---|---|---|---|---|
| ADSL | STUDYID | Study Identifier | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADSL | USUBJID | Unique Subject Identifier | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADSL | ARM | Description of Planned Arm | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADSL | TOTDOSE | Total Dose Administered | numeric | Set per constructed row; see the Row construction sheet. | Derived |
| Template | Include when | STUDYID | USUBJID | ARM | TOTDOSE |
|---|---|---|---|---|---|
| subject | Copy EX.STUDYID | Copy EX.USUBJID | Copy ARM from the RAND record whose SITEID equals EX.SITEID and USUBJID equals EX.USUBJID, and no match yields blank | Aggregate SUM(EX.EXDOSE) over records matching on the shared output keys |
| Version | Date | Author | Description | Reviewer | Sign-off |
|---|---|---|---|---|---|
| 1.7 | 2026-10-20 | yamaa docs build | Read a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default | ||
| 1.6 | 2026-10-17 | yamaa docs build | Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight | ||
| 1.5 | 2026-10-17 | yamaa docs build | Name collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part | ||
| 1.4 | 2026-10-15 | yamaa docs build | State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks | ||
| 1.3 | 2026-09-29 | yamaa docs build | Show study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata | ||
| 1.2 | 2026-09-29 | yamaa docs build | Classify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived | ||
| 1.1 | 2026-09-29 | yamaa docs build | Resolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML | ||
| 1.0 | yamaa docs build | Initial generation from spec.yaml |