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: Would a real study need this derivation, specified this way? Does it follow CDISC ADaM: variable names, controlled terms, record structure? Flag any rule that is ambiguous or that a sponsor would handle differently.
  2. Inputs: Do they look like data collected in a real trial, and do they include the situations you would expect to meet in one?
  3. Expected output: Would independent QC programming reproduce every value from these inputs and rules?

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

Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

Goal: demonstrate a study level changing details inside inherited columns - AVAL, ANRIND, and PARCAT1.

Input: three spec files, read root-first:

  • spec_organization.yaml turns the laboratory test code, result, and reference range indicator into PARAMCD, AVAL, ANRIND, and PARCAT1, reading the indicator without regard to letter case; it marks AVAL as the analysis value and checks that it is not negative;
  • spec_compound.yaml adds the low reference range wording the organization does not list, and notes that AVAL comes from the central laboratory;
  • spec_study.yaml is the entry: it applies one corrected result, marks AVAL as adjudicated and checks that it is never missing, leaves an unrecognized indicator empty, states PARCAT1 as the one category this study collects, and declares the complete output.

Parents resolve depth-first, left to right, with later levels winning; the chain resolves to expected/spec_resolved.yaml, the default view in the specification dropdown.

Note: a later level composes a column detail by detail. The added reference range wording joins the two the organization already lists, the three annotations on AVAL accumulate, and the case-insensitive reading survives a level that never mentions it. A level naming a different way to produce a value replaces it whole instead, which is why PARCAT1 stops reading the test code. Lists never accumulate: the study's own check on AVAL replaces the organization's.

Inputs

Under review
1 source file

input/lb.csv

Edit
4 rows
input/lb.csv
USUBJIDLBTESTCDLBSTRESNLBSTRESULBNRIND
ALT12.5U/Ln
AST-1.0U/Lh
ALT21.0U/Ll
AST30.0U/Lx

Expected output

Under review
4 expected rows

expected/adlb.csv

Edit
4 rows
expected/adlb.csv
USUBJIDPARAMCDAVALANRINDPARCAT1
ALT12.5NORMALCHEMISTRY
AST31HIGHCHEMISTRY
ALT21LOWCHEMISTRY
AST30—CHEMISTRY
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
ADLBAVALIf USUBJID = '01' AND PARAMCD = 'AST' then "31.0"; otherwise "LB.LBSTRESN".Derived
ADLBANRINDRecode None: ; missing or unlisted values stay missing.Derived
ADLBPARCAT1Set constant value "CHEMISTRY".Assigned
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

yamaa code

Runs the yamaa specification; its result must match the expected output

run.R

Edit
4 lines
library(yamaa)adlb <- yamaa_domain("spec_study.yaml")$outputadlb

run.py

Edit
4 lines
import yamaaadlb = yamaa.yamaa_domain("spec_study.yaml").outputadlb