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Standards in this guide are end-to-end implementations of CDISC models designed to ensure the traceability and transparency of data across activities in the data lifecycle. Implementation of models per this guide in relation to activities which support collection, tabulation, analysis, and exchange of data are further described in the table below.
Observations
| Metadataspec |
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| Standards for Collection | Standards for Tabulation | Standards for Analysis |
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CDISC CDASH Model - In this guide, the CDASH Model is implemented to support development of CRFs for the Product Impact on Individual Health use case only. The CDASH Model is the earliest model implemented for this use case.
- The CDASH Model defines a basic set of data collection fields that are expected to be present on the majority of CRFs.
- The use of CDASH data collection fields and variables facilitates mapping to tabulation datasets implemented from the SDTM.
- When data can be collected as it will be represented in a tabulation dataset, with no transformations or derivations, the TIG SDTM variable names are presented in the TIG CDASH to collect the data.
- In cases where collected data must be transformed or reformatted prior to inclusion in a tabulation dataset, or where a corresponding SDTMIG variable does not exist, CDASH has created standardized data collection variable names.
| CDISC SDTM - The SDTM is implemented for use cases
| CDISC ADaM | | Standards for Data Exchange |
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The timing variables included in CDASH Model Section 2.7, Timing (https://www.cdisc.org/standards/foundational/cdash) are available for use in any CRF based on 1 of the 3 general observation classes, except where specific domain restrictions are noted in the SDTMIG. In general, all domains based on the 3 general observation classes should have at least 1 timing variable.
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