Reject a quantile beyond the greatest value

Review ask

As a clinical trial statistician or programmer, answer two short questions in Your review: the task and the inputs. Agreeing with both approves this benchmark; disagreeing with either needs a comment. Propose a fix with the Edit button on any source file, or add it to your comments.

We suggest spending no more than 5 minutes on a review. The other tabs beside Your review are background for assessment, not under review.

Summary

EditUnder reviewWhat this benchmark means

README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: carry each laboratory result into AVAL and add AVALFNC, the upper outlier fence of the parameter's results across subjects.

Input: one alanine aminotransferase (ALT) result per subject.

Variables:

AVALFNC would be the parameter's upper outlier fence, the third quartile plus 1.5 times the interquartile range. The request instead asks for the quantile at 1.5, and a quantile is a proportion of the sorted values from 0 through 1, so the run is rejected before any data is read.

How to fix

State the fence as the formula it is: the third quartile plus 1.5 times the distance between the first and third quartiles.

- name: AVALFNC
  type: float
  derivation:
    aggregate:
      group_by: [PARAMCD]
      expr: "Q3(AVAL) + 1.5 * (Q3(AVAL) - Q1(AVAL))"

If a high percentile was meant instead, write it as a proportion, such as quantile: 0.95 beside QUANTILE(AVAL) for the 95th percentile.

Expected failure

Editthe run is rejected; no artifact is accepted

expected/error.yaml

phase: validation
condition: invalid_field_type
rule: FORMULA-18

expected/error.yaml

phase: validation
condition: invalid_field_type
spec_paths:
  - columns.AVALFNC.derivation.aggregate.quantile
rule: FORMULA-18
context:
  expected: a number from 0 through 1

YAML specification

1 spec file

spec.yaml

Edit44 lines

1yamaa: "1.0"2type: spec3model: ADaM4domain: ADLB5keys: [STUDYID, USUBJID, PARAMCD]6input:7  LB: {path: input/lb.csv, types: {LBSTRESN: float}}89output:10  path: adlb.csv11  columns: [STUDYID, USUBJID, PARAMCD, AVAL, AVALFNC]1213columns:14  - name: STUDYID15    type: str16    label: Study Identifier17    derivation: LB.STUDYID1819  - name: USUBJID20    type: str21    label: Unique Subject Identifier22    derivation: LB.USUBJID2324  - name: PARAMCD25    type: str26    label: Parameter Code27    derivation: LB.LBTESTCD2829  - name: AVAL30    type: float31    label: Analysis Value32    derivation: LB.LBSTRESN3334  # Meant as the upper outlier fence, 1.5 interquartile ranges above the35  # third quartile; a quantile is a proportion from 0 through 1, so the run36  # is rejected before any data is read.37  - name: AVALFNC38    type: float39    label: Upper Outlier Fence of Analysis Value40    derivation:41      aggregate:42        group_by: [PARAMCD]43        quantile: 1.544        expr: "QUANTILE(AVAL)"

Inputs

Under review1 source file

input/lb.csv

Edit4 rows

input/lb.csv
STUDYID	LBTESTCD	LBSTRESN
YAMAA-01	ALT	22
YAMAA-01	ALT	31
YAMAA-01	ALT	118
YAMAA-01	ALT	27

Unexpected Output

Under reviewNo artifact is produced

No fixture files in this directory.

Shaded columns are derived— = missing value

Human review and assessment

Dataset Name	Variable Name	Variable Label	Type	Computational Method	Origin
ADLB	STUDYID	Study Identifier	character	Copy value from LB.STUDYID.	Predecessor
ADLB	USUBJID	Unique Subject Identifier	character	Copy value from LB.USUBJID.	Predecessor
ADLB	PARAMCD	Parameter Code	character	Copy value from LB.LBTESTCD.	Predecessor
ADLB	AVAL	Analysis Value	numeric	Copy value from LB.LBSTRESN.	Predecessor
ADLB	AVALFNC	Upper Outlier Fence of Analysis Value	numeric	Aggregate QUANTILE(AVAL) over records grouped by PARAMCD, matching on the shared output keys.	Derived

Version	Date	Author	Description
1.7	2026-10-20	yamaa docs build	Read a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.6	2026-10-17	yamaa docs build	Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.5	2026-10-17	yamaa docs build	Name collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.4	2026-10-15	yamaa docs build	State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
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/lb.csv

Your review

Mapping spec