Reject Age Bands for a Missing Age

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.

Task: Is this a specification error a study team could realistically make, and should the build stop on it rather than continue?
Inputs: Do they trigger the failure for the reason the summary gives?
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

EditUnder reviewWhat this benchmark means

README.md

Goal: build AGEGRP to place each subject into an age band, with younger below 65 and elderly at or above 65.

Input: collected demographics carrying numeric age (AGE).

Variables:

AGEGRP would place each subject into younger (below 65) or elderly (65 and over). A subject with no recorded age cannot be placed into a band and no fallback is stated, so the run is rejected with no artifact accepted.

How to fix

Decide what the band means for a subject with no recorded age, then say so. To record the band as unknown for that subject:

cut:
  source: AGE
  breaks: [65]
  labels: [younger, elderly]
  missing: unknown

Expected failure

Editthe run is rejected; no artifact is accepted

expected/error.yaml

phase: cut
condition: missing_input
requirement: REQ-0334

expected/error.yaml

phase: cut
condition: missing_input
spec_paths:
  - columns.AGEGRP.derivation.cut
requirement: REQ-0334
context:
  variable: AGE

YAML specification

1 spec file

spec.yaml

Edit37 lines

1schema_version: "1.0"2domain: ADSL3keys: [STUDYID, USUBJID]4input:5  DM: input/dm.csv67output:8  path: adsl.csv9  columns: [STUDYID, USUBJID, AGEGRP]1011columns:12  - name: STUDYID13    type: str14    label: Study Identifier15    derivation: DM.STUDYID1617  - name: USUBJID18    type: str19    label: Unique Subject Identifier20    derivation: DM.USUBJID2122  # The age read as a number, which the banding below needs.23  - name: AGE24    type: int25    label: Age26    derivation: DM.AGE2728  # Below 65 is younger, 65 and over elderly. No band is stated for a missing29  # AGE, so a subject with no recorded age stops the run.30  - name: AGEGRP31    type: str32    label: Age Group33    derivation:34      cut:35        source: AGE36        breaks: [65]37        labels: [younger, elderly]

Inputs

Under review1 source file

input/dm.csv

Edit4 rows

input/dm.csv
STUDYID	AGE	SEX
YAMAA-01	72	M
YAMAA-01	—	F
YAMAA-01	65	F
YAMAA-01	34	M

Unexpected Output

Under reviewNo artifact is produced

No fixture files in this directory.

Shaded columns are derived— = missing value

Comments and assessment materials

Dataset Name	Variable Name	Variable Label	Type	Computational Method	Origin
ADSL	STUDYID	Study Identifier	character	Copy value from DM.STUDYID.	Predecessor
ADSL	USUBJID	Unique Subject Identifier	character	Copy value from DM.USUBJID.	Predecessor
ADSL	AGEGRP	Age Group	character	Band AGE at 65 into "younger" and "elderly", intervals closed on the left.	Derived

Version	Date	Author	Description
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

How to fix

input/dm.csv

Comments

Mapping spec