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 the per-record derive step of an aggregation: convert each record's date to an integer day count with to_epoch_day, then summarize the integers.

Input: exposure records with sequence numbers (EXSEQ) and start dates (EXSTDT). Only the record with sequence number 1 becomes an output row.

Variables:

  • EXSEQ: the exposure sequence number, carried through.
  • EXSTDY: the exposure start date as a count of days since 1970-01-01 (zero on that day, negative before it), blank when the start date is missing. It is not a day counted from a reference start.

Note: each matching exposure record's date is turned into its day count first, so the summary works on plain integers and never on dates. The summary then keeps the value of the one record with the row's subject and sequence number (ONLY); a second matching record would stop the run.

Inputs

Under review
1 source file

input/ex.csv

Edit
3 rows
input/ex.csv
STUDYIDUSUBJIDEXSEQEXSTDT
PILOT712024-01-15
PILOT722024-01-16
PILOT732024-01-17

Expected output

Under review
1 expected row

expected/adex.csv

Edit
1 row
expected/adex.csv
STUDYIDUSUBJIDEXSEQEXSTDY
PILOT7119737
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
ADEXSTUDYIDStudy IdentifiercharacterCopy value from EX.STUDYID.Predecessor
ADEXUSUBJIDUnique Subject IdentifiercharacterCopy value from EX.USUBJID.Predecessor
ADEXEXSEQSequence NumbernumericCopy value from EX.EXSEQ.Predecessor
ADEXEXSTDYEpoch Day of Exposure StartnumericAggregate ONLY(EPOCHDAY) over records matching on STUDYID, USUBJID and EXSEQ, with EPOCHDAY as days since 1970-01-01 for EX.EXSTDT.Derived
TemplateInclude when
exposureEX.EXSEQ = 1
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)adex <- yamaa_domain("spec.yaml")$outputadex

run.py

Edit
4 lines
import yamaaadex = yamaa.yamaa_domain("spec.yaml").outputadex