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The design of analysis datasets is generally driven by the scientific and medical objectives of the study.

Jira
showSummary false server Issue Tracker (JIRA) serverId 85506ce4-3cb3-3d91-85ee-f633aaaf4a45 key TOBA-74

A  A fundamental principle is that the structure and content of analysis datasets must support clear, unambiguous communication of the scientific and statistical aspects of the study. The purpose of ADaM is to provide a framework that both enables analysis of the data and allows reviewers and other recipients of the data to have a clear understanding of the data’s lineage from collection to analysis to results. ADaM provides the core and defines the spirit and intent of its concepts and standards. The model outlines the fundamental principles to follow in constructing analysis datasets and related metadata. Four types of metadata—analysis dataset metadata, analysis variable metadata, analysis parameter value-level metadata, and analysis results metadata—are described in ADaM. To establish which components are required in a submission, review current relevant files provided by the agency to which the submission is being sent. Other relevant documentation might include the study protocol, the statistical analysis plan (SAP), mock shells that define desired outputs, and any dataset specifications that have been defined.

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