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

Take some time out to attend a 4-day workshop in beautiful Tyrol, Austria.  

Image: Austria / Tyrol by Karsten H.68

The Course Faculty is:

• Uwe Siebert, MD, MPH, MSc, ScD Professor of Public Health, UMIT, Hall i. T., Austria
• Nicholas Latimer, BSc, MSc, PhD Senior Research Fellow, University of Sheffield, UK
• Ian White, MA, MSc, PhD Program Leader, MRC Biostatistics Unit, Cambridge, UK

This 4-day Course is on 3-6 May 2016 and will be held in Tyrol, Austria.

The workshop combines lectures, discussions, exercises, and hands-on computer lab sessions in the key elements and methods of Causal Inference and covers the following subjects:

• Concepts and methods of causality, counterfactuals and causal inference
• Framing and interpreting causal research questions
• The use of causal diagrams (directed acyclic graphs, DAGs)
• The paradigmatic shift from traditional statistical analysis to causal analysis and   the difference between naive methods and causal methods
• Adjustment for fixed and time-varying confounding and treatment switching/adherence
• The use of causal methods (g-formula, inverse probability weighting with marginal structural models, g-estimation with structural nested models)
• Applying publicly available software to case examples
• Programming analyses in STATA using inverse probability weighting (IPW) for marginal structural models (MSM) and g-estimation for rank-preserving structural failure time models (RPSFTM)
• How to identify the appropriate adjustment method
• Recommendations and guidelines on adjustment methods

Online booking for this course is available here.