Datamanagement

The upstream process of collecting and cleaning data merits particular attention as the value of the statistical analysis is directly related to the quality of the data being analyzed. It is therefore important to recognize systematic error sources at an early stage. Other focal points include ensuring the completeness of data and giving special attention to any and all information used for calculating the primary endpoint variable.

CDISC standards gain in importance and are mandatory for most studies. Taking this into account during database setup and applying CDASH standard facilitates the subsequent processes enormously and improves quality and tracebility.

 

  • Support of data validation by identifying data issues and creation of listings
  • Specification and creation of SDTM datasets, annotated CRF, generation of define.xml
  • Creation of patient profiles
  • Creation of narratives
  • Creation of routine reports

 


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