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Clinical SAS Training in Chennai

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Prerequisites for learn SAS Clinical Certification

Clinical SAS Programming professionals should have little knowledge in clinical studies and should have basic knowledge in the process of making clinical study , be familiar  with the SAS clinical Programming Basics.

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Who should attend this SAS Clinical Training :
 
  • Life science Graduates and Bioinformatics
  • Job Aspirants along with the basic clinical programming concepts and the statistics SAS Clinical research metadata and data. It also provides the needed foundations that helps in ensuring standard and trusted clinical data that supports the strategic analyses such as cross study of the advanced analysis that are more safety. With our SAS Clinical Programming students can gain both efficiency and speed and  performing automatic repeatable data Integration tasks.
 

Clinical SAS Training Duration

 
Regular Batch - Daytime, Morning and Evening
 
  • Time Duration : 45 hours
Weekend Batches - Saturday and Sunday & Holidays
 
  • Time Duration : 9 weeks
Fast Track course Training - (daily 5+ hours)
 
  • Time Duration : 2 weeks
 
#MODULE - 1
SAS Programming
  • Standardized approach for analysis files
  • Programming based on analysis data
  • Programming for integrated summary of safety and efficacy
  • Independent quality reviews
  • Customized clinical data outputs
  • Transportable tools to support standard non-efficacy reports
  • Proactive, results-oriented approach to programming
  • Programming based on data validation plan
 
#MODULE - 2
Clinical SAS Data Integration
  • Register source data and target tables
  • Work with many of the various transformations
  • Document and deploy jobs
  • Enhance table relationships using integrity constraints, key, and indexes
  • Work with slowly changing dimensions
  • Create jobs and explore the functionality of the Job Editor
  • Administer SAS Data Integration Studio
 
#MODULE - 3
Biostatistics
  • Consultation on study design
  • DSMB participation
  • Randomization
  • Statistical Analysis Plan
  • Protocol development
  • Interim analysis
  • Sample size calculations
 
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