The Supplemental Qualifiers (SUPP–) special purpose dataset model is used to represent both nonstandard variables (NSVs) and attributions with their relationship to records in a parent dataset.
In a SUPP-- dataset, the combined set of values for STUDYID, USUBJID, POOLID (for nonclinical studies only), IDVAR, IDVARVAL, and QNAM will be unique for every record. There will not be multiple records in a SUPP-- dataset for the same QNAM value, as it relates to IDVAR/IDVARVAL for a USUBJID in a domain. Using --GRPID can be a more efficient method to identify individual qualifier values (SUPP-- records) related to multiple general observation class domain records that could be grouped, such as relating an attribution to a group of laboratory measurements.
Nonstandard Variables
SUPP-- represents the metadata and data for each NSV/value combination and relates this to the observation or observations qualified by the NSV in the parent dataset. Each SUPP-- dataset record also includes the name of the qualifier variable being added (QNAM), the label for the variable (QLABEL), the actual value for each instance or record (QVAL), the origin (QORIG) of the value, and the evaluator (QEVAL) to specify the role of the individual who assigned the value when the value is assigned. Gary - How can we describe origin here? Can we simply refer to Define-XML?
Attributions
An attribution is typically an interpretation or subjective classification of 1 or more observations by a specific evaluator. A SUPP-- dataset can contain both objective data (where values are collected or derived algorithmically) and subjective data (attributions where values are assigned by a person or committee). For objective data, the value in QEVAL will be null. For subjective data, the value in QEVAL should reflect the role of the person assigning the value.
Overview
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