Conformance to Standards

In this section, conformance refers to whether implementation of standards per this guide meets the requirements of the standards. Conformant collection and representation of tobacco product study data is ensured by full adherence to standards per this guide. Conformance to standards is assessed by confirming implementation of standards per this guide and by evaluating tabulation and analysis data in relation to conformance rules.

For data collection using CRFs, conformance to standards is minimally ensured by:

Num	Conformance	Implementation
1	Following TIG Core designations.	All HR (Highly Recommended) and applicable R/C (Recommended/Conditional) data collection fields are present in the CRF and/or operational database.
2	Following guidance for CDISC Controlled Terminology.	Controlled terminology is used as specified to collect the data using the CRF.
3	Following best practices for CRF design.	The design of the CRF follows both recommendations for creating data collection instruments and recommendations for CRF design.
4	Following standard wording for Question Text or Prompts.	The wording of CRF questions is standardized per specified Question Text or Prompts for the data collection fields.
5	Following Data Collection Variable naming conventions.	Data Collection Variable naming conventions are applied in the operational database as specified.
6	Aligning data collection variables values and target tabulation variables values when collection and tabulation variable names are the same. Minimal processing, such as changing case when mapping a data collection variable value into a tabulation variable, does not affect conformance.	Data output by the operational database into a tabulation dataset variable requires minimal processing when the data collection and tabulation variable names are the same.
7	Presenting validated QRS questions and reply choices as validated in the CRF. In some cases, this may result in CRFs that do not conform to CDASH best practices. The use of such questionnaires in their native format does not affect conformance.	All QRS questions and reply choices are presented as validated in the CRF.

For tabulation datasets, conformance to standards is minimally ensured by:

Num	Conformance	Implementation
1	Representing of all collected, assigned, and relevant derived data in applicable datasets.	Representing of all collected, assigned, and relevant derived data in applicable datasets.
	Following the complete metadata structure for data domains
	Following SDTMIG domain models wherever applicable
		Using specified standard domain names and prefixes per controlled terminology where applicable
		Following SDTM-specified controlled terminology and format guidelines for variables, when provided
	Using specified standard variable names
	Using specified standard variable labels
	Including all Required and Expected variables as columns in standard domains, and ensuring that all Required variables are populated
	Ensuring that each record in a dataset includes the appropriate Identifier and Timing variables, as well as a Topic variable
	Conforming to guidance in CDISC Notes column and general and domain-specific assumptions

For analysis datasets, conformance to standards is minimally ensured by:

Tabulation and analysis dataset conformance can be formally evaluated by comparing dataset content in relation to conformance rules.

<Add references to conformance rules here>

Page tree

Conformance to Standards