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To use standards for analysis one must understand that the design of analysis datasets is generally driven by the scientific and medical objectives of the clinical study.

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

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

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