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Conformant collection and representation of tobacco product 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 The following table illustrates minimum conformance to standards for data collection using CRFs, conformance to standards is minimally ensured by: .

Metadataspec
NumConformanceImplementation
1Following Best Practices best practices for CRF design.

The design of the CRF follows both recommendations for creating data collection instruments and recommendations for CRF design.

2Following Data Collection Variable data collection variable naming conventions.

Data Collection Variablecollection variable naming conventions are applied in the operational database as specified.

3Following standard wording for Question Text or Prompts.question text or prompts

The wording of CRF questions is standardized per specified Question Text question text or Prompts prompt for the data collection fields.

4Following Core core designations.

All HR (Highly Recommended) and applicable R/C (Recommended/Conditional) data collection fields are present in the CRF and/or operational database.

5Following guidance for CDISC Controlled Terminology.

Controlled terminology is used as specified to collect the data using the CRF. 

6

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. 

7

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. 


For tabulation datasets, The following table illustrates minimum conformance to standards is minimally ensured by:for tabulation datasets. 

Metadataspec
NumConformanceImplementation
1

Representing all collected, assigned, and relevant derived data in applicable datasets.

All data generated per scientific and regulatory requirements are included in tabulation datasets.
2

Using domain specifications in this guide wherever applicable.

A dataset is created using a domain specification in this guide when the scientific nature or role of the data is within the scope of a domain. Domains are extended or custom domain specifications are only used when data are different in nature and are not in scope for domains in this guide.

3

DM is created.

For studies that assess the impact of tobacco products on the health of individuals, DM is required even if no other datasets are generated. 
4

Following conventions for dataset naming.

The dataset name is standardized per naming conventions and per controlled terminology where applicable.
5

Following guidance for dataset record structure.

Dataset content is aligned with the record structure specified per the domain specification.
6Following Core core designations.

All Required and Expected tabulation variables are included as columns in the dataset. Required tabulation variables are populated for all records in the dataset. Permissible variables  variables used to collect data are included in the dataset, even when no data for those variables were collected.

7Following conventions for variable naming.The names of variables in the dataset are standardized per domain specifications and other applicable guidance. Controlled terminology for domain prefixes is used as specified for variable naming.
8Following conventions for variable labels.The labels for variables in the dataset are standardized per domain specifications and other applicable guidance. 
9

Following guidance for variable types.

The variables in the dataset are standardized for either numeric or character values as specified per the domain specification.

10

Populating variable values in alignment with this guide

All variables in the dataset are populated as expected per this guide including per general and domain-specific guidance, controlled terminology, and formatting.

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