Review ask

As a clinical trial statistician or programmer, challenge anything in this benchmark: describe a problem in Comments, or propose a fix with the Edit button on any source file.

  1. Task: Is this a specification error a study team could realistically make, and should the build stop on it rather than continue?
  2. Inputs: Do they trigger the failure for the reason the summary gives?
  3. Expected failure: Is this the right error, raised at the right point, and would it tell the programmer what to fix?

The other tabs beside Comments are background for assessment, not under review.

Summary

Lifecycle: reviewedEditUnder review
What this benchmark means
README.md

Goal: one analysis record for each collected event, carrying the start-date completeness flag ASTDTF.

Input: collected event records carrying the reported term (AETERM) and the collected start (AESTDTC).

Variables:

  • ASTDTF would contain how much of the start date AESTDTC carries: D for a full date, M for a year and month, Y for a year alone, and blank when the start was never collected. Text that is neither a date nor the beginning of one has no completeness to report, so the run stops when it tries to read precision from it and no artifact is accepted.

How to fix

Correct the source text when a date can be recovered. If invalid date text is intentionally represented by a missing precision flag, declare that separately from the existing missing-source behavior:

date_precision:
  source: AE.AESTDTC
  missing: null
  invalid: null

The invalid outcome covers UNK; missing covers a source value that was not collected.

Expected failure

Edit
the run is rejected; no artifact is accepted
expected/error.yaml
phase
impute
condition
invalid_date_text
requirement
REQ-0588
expected/error.yaml
phase: impute
condition: invalid_date_text
spec_paths:
  - columns.ASTDTF.derivation.date_precision
requirement: REQ-0588
context:
  source: AE.AESTDTC
  value: UNK
  keys:
    - STUDYID: PILOT7
      USUBJID: P7-341
      AESEQ: 2

Inputs

Under review
1 source file

input/ae.csv

Edit
2 rows
input/ae.csv
STUDYIDUSUBJIDAESEQAETERMAESTDTC
PILOT71Nausea2023-06
PILOT72FatigueUNK

Unexpected Output

Under review
No artifact is produced

No fixture files in this directory.

Shaded columns are derived— = missing value

Comments and assessment materials

Comments

Signed in with GitHub; saved in repository Discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Dataset NameVariable NameVariable LabelTypeCodelist/Controlled TermsCoreComputational MethodOrigin
ADAESTUDYIDStudy IdentifiercharacterCopy value from AE.STUDYID.Predecessor
ADAEUSUBJIDUnique Subject IdentifiercharacterCopy value from AE.USUBJID.Predecessor
ADAEAESEQSequence NumbernumericCopy value from AE.AESEQ.Predecessor
ADAEASTDTFAnalysis Start Date Imputation FlagcharacterCollected date precision of AE.AESTDTC: D for a complete date, M for year and month, Y for a year alone; a missing source → blank.Derived
VersionDateAuthorDescriptionReviewerSign-off
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml