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Standards in this guide are aligned with both use cases and activities. Given this, determining which of standards to use may begin with selecting standards appropriate to both the use case and activity. The table below shows use cases and activities aligned with sections of this guide in which detailed instructions for implementation may be found. Sections referenced in this table are:

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Observations about products, Standards for collection, tabulation, and analysis collect and represent data by common topics with standards for collection and tabulation grouping logically related data in domains and the design of analysis datasets customizable per analysis requirements. Standards for data exchange are applicable to all use cases and support exchange of CRFs,  

A domain is defined as a collection of logically related observations with a common topic. 

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Standards for data collection and tabulation are At the highest level, use cases addressed in the TIG are aligned with data-related activities supported by the standards. use cases inherent to studies of tobacco productsboth tobacco study use cases and by data related processes they support. In the TIG:  

Use cases, activities, and associated sets of standards in scope for this guide are shown in the table below.

Observations and Variables - SDTMIG v3.4 - Wiki (cdisc.org) The SDTMIG for Human Clinical Trials is based on the SDTM’s general framework for organizing clinical trial information that is to be submitted to regulatory authorities. The SDTM is built around the concept of observations collected about subjects who participated in a clinical study. Each observation can be described by a series of variables, corresponding to a row in a dataset. 

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Determining Where Data Belong

Standards for collection, tabulation, and analysis collect and represent data by common topics with:

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Domains

SDTM

Observations about study subjects are normally collected for all subjects in a series of domains. A domain is defined as a collection of logically related observations with a common topic. The logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial. Each domain is represented by a single dataset.

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