Causal inference with compositional data
- Lecture Series – Causal Inference Methods For Real-World Data
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Speakers
Research Fellow at the UCL Centre for Longitudinal Studies
Co-leader of the Causal Inference Interest Group
Abstract
Compositional data is a form of hierarchical data in which a whole (or a total) is the sum of its constituent components. Although compositional data can arise in any setting, they
are particularly common in health research, with typical examples including dietary, physical activity, or microbiome data. This type of data can bring a range of analytical and interpretational challenges which risks
results being misinterpreted.
In this talk, I will introduce compositional data using directed acrylic graphs (DAGs), outline the different types of causal effects that may be of interest in such data, and discuss suitable analytical approaches.
Host
Responsible Scientist
LOCATION
Lecture:
Room: Maison des Sciences Humaines
11, porte des sciences
L-4366 Esch- sur- Alzette, Luxembourg
LECTURE: 11:00am – 12:00pm
Webinar via Webex:
Event number: 2789 913 4500
Event password: 3y7hPPbtkf3
MEET & EAT
12:00pm – 13:30pm
Room: Maison des Sciences Humaines
11, porte des sciences
L-4366 Esch- sur- Alzette, Luxembourg
Light lunch provided – *Please note that registration for Meet and Eat is mandatory via the following link:
Supported by:
