Süßmilch Lecture - hybrid

Expert-driven versus Data-driven Causal Graph Selection in Epidemiology

Vanessa Didelez, Leibniz-Institute of Prevention Research and Epidemiology – BIPS
Online or at Max Planck Institute for Demographic Research, February 25, 2025

As part of the Suessmilch Lecture series, Vanessa Didelez from the Leibniz-Institute of Prevention Research and Epidemiology – BIPS will present on the subject of expert-driven versus data-driven causal graph selection in epidemiology.

The event begins at 3 pm CEST on February 25, 2025.

Abstract

In this talk Vanessa Didelez will address the role of causal graphs and causal discovery and review current use and needs in the field of Epidemiology. Here, we often aim to address causal research questions with observational, incomplete, and temporally structured databases. Many analyses procede with a causal model that is entirely based on expert knowledge, while data-driven approaches are not yet established or used in Epidemiology. However, building a causal model, determining sufficient and efficient adjustment sets, and (nonparametrically) estimating causal effects are key tasks. I will review the strengths and weaknesses of expert-driven versus data-driven approaches, and how they may be combibed. Moreover, this has led to recent advances and new insights into methods of causal inference and causal discovery.

About the Speaker

Vanessa Didelez is Professor of Statistics and Causal Inference at the Leibniz-Institute of Prevention Research and Epidemiology – BIPS, Bremen, Germany, in a joint appointment with the Department of Mathematics and Computer Science of the University of Bremen. She graduated in the subject of Statistics with Psychology and received her PhD in Statistics from the University of Dortmund, Germany.

She spent 16 years in the UK, first at the Department of Statistical Science, University College London, and then at the Department of Mathematics at the University of Bristol. She was appointed at BIPS in 2016, where she is Deputy Head of the Department of Biometry and Data Management. She has held numerous grants, most recently on "Causal discovery across the lifespan" funded by the German Research Foundation. Her research combines many aspects of causal inference, graphical modelling, and time-structured / time-to-event data with applications in epidemiology.

Participation

Please register via this survey for online participation. The Zoom link will be sent to you afterwards. The event begins at 3 pm CEST on February 25, 2025.