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The Association of Schools of Public Health in the European Region (ASPHER)

ASPHER is the key independent European organisation dedicated to strengthening the role of public health by improving education and training of public health professionals for both practice and research.
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Causal Inference for Assessing Effectiveness in Real World Data and Clinical Trials: A Practical Hands-on Workshop
When: 16 Mar 2020 - 20 Mar 2020
Organiser: HTADS Continuing Education Program
Contact: htads@umit.at

Reminder: Early Booking Deadline until 24 February 2020

Dear Colleagues,

We are pleased to announce our 5-Day Certificate Course "Causal Inference for Assessing Effectiveness in Real World Data and Clinical Trials: A Practical Hands-on Workshop", 16-20 March 2020 to be held in Hall in Tirol, Austria.

Course Directors:
Uwe Siebert, MD, MPH, MSc, ScD Professor of Public Health, UMIT
Nicholas Latimer, BSc, MSc, PhD Senior Research Fellow in Health Economics, Health Economics and Decision Science, University of Sheffield, UK
Ian White, MA, MSc, PhD 
Professor of Statistical Methods for Medicine
MRC Clinical Trials Unit at University College London


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
  • Use of causal diagrams (directed acyclic graphs, DAGs) in observational studies and clinical trials
  • 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
  • Use of causal methods (g-formula, inverse probability weighting with marginal structural models, g-estimation with structural nested models)
  • The target trial concept
  • Applying publicly available software to case examples
  • Programming analyses in STATA using inverse probability weighting (IPW) with marginal structural models (MSM) and g-estimation with 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 via www.umit.at/htads


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