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he CDASH Model aligns with and is structured similarly to the SDTM. The CDASH Model organizes data into classes, which represent meaningful groupings of data in clinical research. It defines CDASH metadata for identifier variables, timing variables, general observation class variables (Events, Interventions, and Findings), domain-specific variables, and special-purpose domain variables.

The current CDASH Model represents Identifier, Timing, and Domain-specific variables in the metadata as an Observation Class. This does not align with the SDTM. This will be revised in a future version of the CDASH Model.

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. The scientific subject matter of the data 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.

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