Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching

16-19 April 2018
Hall in Tirol, Austria

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 4-day certiied 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.

Registration for this course can be made online or by fax. Payment details, cancellation policy and registration form in PDF format are available on

Contact & Course Location

Continuing Education Program on
HTA & Decision Sciences (HTADS)

Institute of Public Health, Medical Decision
Making and HTA

UMIT – University for Health Sciences,
Medical Informatics and Technology


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Mark Roberts, MD, MPP
Mark Roberts, MD, MPP
"After 30 years, the world has caught up with what people in SMDM have been doing all along."
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