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Continuing Education Credits are not available for the archived offering.
This program is a part of DIA's Certificate Program and is awarded the following:
Clinical Research Certificate Program: 8 Elective Units
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This archive may be purchased through December 31, 2015.
Archive duration:
Part 1: 1 hour 54 minutes
Part 2: 1 hour 56 minutes
Part 3: 2 hour 1 minute
Part 4: 1 hour 57 minutes
Part 5: 1 hour 57 minutes

This advanced online course answers common questions and addresses topics such as modeling, multiplicity adjustments, noninferiority, data mining, adaptive designs, Bayesian principles, and survival methods. This course will increase the level of statistical knowledge of nonstatisticians so that collaborative efforts of statisticians and nonstatisticians on clinical investigative teams can be improved.

Course Level: Advanced

Featured topics

  • Focuses on answering common questions and addressing topics such as:
    • modeling
    • multiplicity adjustments
    • non-inferiority
    • data mining
    • adaptive designs
    • Bayesian principles
    • survival methods
  • Use knowledge gained from the course to improve your contribution to clinical investigative teams
  • Interactive discussions and activities to practice the concepts
  • Applying advanced statistics to designing studies

Who should attend?

  • Those who have completed Clinical Statistics for Nonstatisticians
  • Clinical research professionals
  • Project managers
  • Decision makers who use statistics to describe potential impact on studies

Learning objectives

At the conclusion of this activity, participants should be able to:

  • Identify ways to use statistics to make better decisions in the drug development process
  • Describe what a statistical model can and cannot do in terms of trial design and management
  • Recognize why multiplicity adjustments may be necessary and identify the pros and cons of these adjustment methods
  • Describe clinical equivalence and non-inferiority clinical trial designs
  • Describe the basis of Bayesian methods
  • Describe how survival trials can be analyzed and adapted
  • Effectively speak to co-workers and management using advanced statistical terms

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