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Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching: A Practical Hands-on Workshop

26 February 2018

The course will take place from 16 to 19 April 2018 at the University for Health Sciences, Medical Informatics and Technology (UMIT), Austria. Ian White, Professor of Statistical Methods for Medicine at MRCCTU at UCL will be teaching on the course.

Causal inference in epidemiology and medicine is the process of drawing a conclusion about a causal connection between an exposure/intervention and an outcome. It provides important information for health policy decision-makers, HTA agencies, clinical guideline developers and researchers to derive valid causal interpretations from study results in health and medicine.

This course covers the key concepts and methodological approaches to causal inference in observational and experimental studies with a specific focus on adjustment for treatment switching in clinical trials. Further aspects include adjustment for time-varying confounding, adjustment for compliance, adjustment for multiple lines of treatments, study design with real world data analysis and the use of causal graphs.

For further information, please visit the course page on the UMIT website.