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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). A variable name, label, and value for the attribution are represented in SUPP-- dataset variables QNAM, QLABEL, and QVAL respectively. The origin for the attribution will be represented in variable QORIG.  For 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

For Interventions and Events general observation class domains, all subjective data are assumed to be attributed to the investigator. For observations that have primary and secondary evaluations of specific qualifier variables, applicants should put data from the primary evaluation into the parent dataset and data from the secondary evaluation into the Supplemental Qualifier datasets (SUPP--). Within each SUPP-- record, the value for QNAM should be formed by appending a "1" to the corresponding standard domain variable name. In cases where the standard domain variable name is already 8 characters in length, applicants should replace the last character with a "1" (incremented for each additional attribution).

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