Reject NA 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: carry AGE unchanged for analysis, keeping the collected age for each subject.

Input: collected demographics records holding AGE.

Variables:

AGE would contain the collected age copied from the collected records, but a stored age of NA is not a number, so the run stops while reading the stored value and no artifact is accepted.

How to fix

Leave the field empty when an age was not collected, and keep reading the field as a number:

input:
  DM:
    path: input/dm.csv
    types:
      AGE: int

If the code carries a meaning worth keeping, such as an age withheld rather than never taken, read the field as text and map the code to a value the study defines.

Expected failure

Editthe run is rejected; no artifact is accepted

expected/error.yaml

phase: ingest
condition: field_parse_failed
requirement: REQ-0536

expected/error.yaml

phase: ingest
condition: field_parse_failed
spec_paths:
  - input.DM.types.AGE
requirement: REQ-0536
context:
  dataset: DM
  field: AGE
  type: int
  value: "NA"

YAML specification

1 spec file

spec.yaml

Edit25 lines

1schema_version: "1.0"2domain: ADSL3keys: [STUDYID, USUBJID]4input:5  DM: {path: input/dm.csv, types: {AGE: int}}67output:8  path: adsl.csv9  columns: [STUDYID, USUBJID, AGE]1011columns:12  - name: STUDYID13    type: str14    label: Study Identifier15    derivation: DM.STUDYID1617  - name: USUBJID18    type: str19    label: Unique Subject Identifier20    derivation: DM.USUBJID2122  - name: AGE23    type: int24    label: Age25    derivation: DM.AGE

Inputs

Under review1 source file

input/dm.csv

Edit2 rows

input/dm.csv
STUDYID	USUBJID	AGE
CTX		64
CTX		NA

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	AGE	Age	numeric	Copy value from DM.AGE.	Predecessor

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