Skip to main content

Detailed Information

  • November 11, 2018
    1:00pm - 5:00pm
    Type: Short Course
    Capacity: 67


    In specific situations, clinical studies need causal inference methods to estimate a valid causal effect of a health intervention. Causal adjustment is needed if there is confounding-by-indication in observational studies or when ITT analyses lead to biased effect estimates in RCTs with noncompliance/treatment switching. Since first HTA agencies have accepted and requested the use of causal methods, a paradigm shift is taking place, and the selection of the appropriate method has become crucial to yield patient access to innovative treatments. This course will (1) introduce causal diagrams as a tool for causal assessment, (2) give an overview on causal methods (e.g., rank preserving structural failure time models, marginal structural models, two-stage approach), (3) present lessons learne...