Course – 11th-13th March 2019 on causal inference: drawing causal conclusions from epidemiological studies

Causal inference is the ultimate goal of most epidemiological studies based on observational data. This course gives an applied introduction to modern methods of causal inference that may help answer casual questions. The course covers a general discussion on how to phrase causal questions and critically evaluate the underlying assumptions. The course will also provide a range of tools to address causality, including Directed Acyclic Graphs [DAGs], pseudo-trials, and mediation analysis. The course also deals with selection and information bias, and looks into different way of integrate results from several different approaches, where each approach has different independent key sources of potential bias, also called triangulation. The course will be centered on the participants’ own research.

Dates: 11th to 13th of March 2019 in Copenhagen

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