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Session 1: An Introduction to Directed Acyclic Graphs (DAGs) for Causal Inference

Led by researchers from the SPACE team, Centre for Public Health, Queen’s University Belfast 

DAGs Workshop – Session 1

What will we do?  

  • we will cover a short introduction to causality 
  • we will learn the essentials of DAGs 
  • we will learn what a confounder, a mediator, and a collider are 
  • we will learn the d-separation rules 
  • we will work with some examples 
  • we will end the session with a DAGitty demonstration that you can replicate at home to create your own DAGs 

Date:  Thursday 11 May @ 15:00 - 17:00hrs (London) / 08:00 - 10:00hrs (PDT) 

Venue:  Online Webinar via Zoom registration 

You have the option to register to attend only Session 1 or both Sessions 1 & 2.  If you are already working with some research questions, we highly encourage you to register for both. 

Registration for both workshops will close:  Tuesday 9 May 2023 @ 23:59hrs (GMT)

Registration Link - Session 1 


Dr Ione Avila-Palencia is a Research Fellow at Queen’s University Belfast working in the SPACE project. She has a background in Environmental Sciences and Public Health. Her research is focused on health effects of urban design, transport and related exposures like air pollution and physical activity in cities. Ione is currently working on the co-creation of a causal loop diagram, the combination of complex systems approach with causal inference tools like DAGs, and the development of mediation analyses about urban environment factors and cognitive decline outcomes. 

Dr Hüseyin Küçükali is a Research Fellow at Queen’s University Belfast working in the SPACE project. He is a public health researcher with experience in artificial intelligence and behavioural science. His research aims to innovate the prevention of diseases and health inequalities. Hüseyin is currently working in the application of the syndemic theory principles to the study of synergistic interactions between physical activity behaviour and cognitive decline, and the edgewise modelling and estimation of total effects within the sub-system of physical activity and cognitive decline. 


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