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Course Catalog

340.676.11 Bayesian Adaptive Trials

Department:
Epidemiology
Term:
Summer Inst. term
Credits:
2 credits
Academic Year:
2019 - 2020
Location:
East Baltimore
Dates:
Mon 06/17/2019 - Fri 06/21/2019
Class Times:
  • M Tu W Th F,  8:30 - 11:50am
Auditors Allowed:
No
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Ayesha Khan
Course Instructor:
  • Jason Connor
Resources:
Description:

Presents Bayesian adaptive designs and teaches students the skills and considerations necessary to construct such designs. Examines the operating characteristics of Bayesian adaptive designs and the benefits and costs of interim analyses, in particular within the regulatory framework.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Demonstrate skills in adaptive designs, Bayesian analysis and Bayesian computation
  2. Assess sets of real-life Bayesian adaptive designs and evaluate considerations that went into each design, and the adaptive decisions that are made in each trial
  3. Be introduced to studies with noncompliance to treatment, and the method of instrumental variables for estimating causal effects
Methods of Assessment:

Exam

Instructor Consent:

No consent required