The scientific subject matter of the data and related activities such as data collection, data tabulation, data analysis, and data exchange drive which standards to implement. Implementation of standards starts with determining which standards are appropriate based on the nature of the data and activities to be supported. After standards are selected, it is then possible to determine how the data are collected, represented, or exchanged using the standards.
Standards in this guide are aligned with both use cases and activities. Given this, determining which standards to use may begin by selecting standards for the use case and activity to be supported. It is recommended that all guidance is reviewed, both higher level and detailed, prior to implementing standards. For ease of use, the table below presents use cases, activities, and corresponding sections in this guide which provide detailed instructions for implementation. Detailed instructions referenced are:
- Section x.x, Standards for Collection, to guide development and use of case report forms (CRFs) by implementing the CDISC CDASH Model.
- Section x.x, Standards for Tabulation, to guide organization of data collected, assigned, or derived for a study by implementing SDTM.
- Section x.x, Standards for Analysis, to specify the principles to follow in the creation of analysis datasets and associated metadata by implementing the ADaM.
- Section x.x, Standards for Data Exchange, to support sharing of structured data between parties and across different information systems by implementing specified standards and resources.
Once standards are selected based on the use case and activity, the scientific subject matter of the data, its role, and analysis needs will determine where data belong, i.e., how the data are collected, represented, or exchanged using the standards. Standards for collection and tabulation collect and represent data in groupings of logically related data called domains. Domains are aligned between collection and tabulation standards to facilitate the transition of collected observations to their representation in tabulation datasets. Standards for analysis are based on analysis requirements with the structure of tabulation datasets facilitating the generation of analysis datasets.
To use standards for collection and tabulation, compare the nature or role of the data to the scope of a domain. A domain standard may be used when the nature of the data and the domain scope are aligned. Observations will be collected using collection standards and represented as rows in tabulation datasets. Each observation is described by a series of data points which correspond to data collection fields and columns in a tabulation dataset.
Fields and variables may be used when
To use standards for analysis,
Observations are described using collection and tabulation variables.
are used to design customized datasets is cucustomizable per analysis requirements.
Analysis needs drive the selection of analysis standards, where analysis requirements are supported by both the structure and the contents of the resulting dataset.
further drives the selection of collection and tabulation standards, where the nature of the data must be within the scope of a domain for the domain to be used. Analysis needs drive the selection of analysis standards, where analysis requirements are supported by both the structure and the contents of the resulting dataset. Standards for data exchange are applicable to all use cases and support sharing of standard CRFs, tabulation datasets, and analysis datasets.
Standards for Collection | Standards for Tabulation | Standards for Analysis | |
---|---|---|---|
Organization of Data |
| ||
Standards for collection and tabulation group logically related data in domains while All standards are designed to flow together - The table below describes
The logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial.
Domains