You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 54 Next »

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 indicated by: 


NumConformanceDescription
1Adherence to 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.

2Adherence to specified use of CDISC Controlled Terminology.

Specified controlled terminology must be used to collect the data in the CRF. 

3Best practices for CRF design are followed.

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

4Adherence to Question Text or Prompts. 

Question Text or Prompts are used to standardize the wording of CRF questions. 

5Adherence to Data Collection Variable naming conventions.

Data Collection Variable conventions are used in the operational database as specified in this guide.

6

Data output by the operational database into a tabulation dataset variable requires minimal processing when the data collection variable and tabulation variables names are the same. 





should requires no additional processing if the CDASH and SDTM variable names are the same. 



  1. An SDTM data programmer should be able to assume that data in an SDTMIG variable is SDTMIG-compliant. Minimal processing (e.g., changing case) does not affect conformance. This helps to ensure a quality deliverable, even if the programmer is unfamiliar with data capture practices.



 should requires no additional processing if the CDASH and SDTM variable names are the same. 



  1. An SDTM data programmer should be able to assume that data in an SDTMIG variable is SDTMIG-compliant. Minimal processing (e.g., changing case) does not affect conformance. This helps to ensure a quality deliverable, even if the programmer is unfamiliar with data capture practices.
7Validated questionnaires, ratings, or scales present the questions and reply choices as validated. 
  1. his must be followed to maintain the validity of a validated instrument. (See Section 8.3.12, QRS - Questionnaires, Ratings, and Scales).
    1. In some cases, this may result in CRFs that do not conform to CDASH best practices; however, restructuring these questionnaires should not be done because it could invalidate them.
    2. The use of such questionnaires in their native format should not be considered to affect conformance to CDASH.



Guidelines for Tabulation Datasets

Tabulation dataset conformance with standards in this guide is minimally indicated by:

  • Representation 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
  • Using specified standard variable names
  • Using specified standard variable labels
  • Following SDTM-specified controlled terminology and format guidelines for variables, when provided
  • 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
  • Conformance Rules





Conformance to standards in this guide can be proactively ensuring


and assessing conformance Conformant collection and representation of data is ensured by full adherence standards per this guide.



Conformance may be by data collection







Conformance to standards may be minimally assessed by confirming intended implementation per the guidelines below and by evaluating tabulation and analysis datasets in relation to conformance rules.


  • No labels