Multilevel Bayesian Networks for Hierarchical Data

Bezalem Eshetu Yirdaw, University of South Africa
Tuesday, 14th April 2026

Register for free: https://BNMAWebinarApr.eventbrite.co.nz

Want to understand how Bayesian networks can handle real‑world multilevel data or data that change over time? This webinar gives you an introduction to Multilevel Bayesian Networks (MBNs) and how they extend traditional BN modelling. Attendees will learn about:

• The core ideas behind Multilevel Bayesian Networks

How MBNs build on standard Bayesian Networks to handle longitudinal and multilevel data structures.

• Why MBNs matter for real datasets

Especially when working with repeated measurements, data grouped by hospitals, villages, or other clusters, or hierarchical study designs.

• How MBNs are applied in practice

Including examples relevant to longitudinal and multilevel data analysis.

A hands‑on demonstration in R showing how to specify and run a Multilevel Bayesian Network.

Bezalem Eshetu Yirdaw is a final-year PhD candidate in the Department of Statistics, University of South Africa, supervised by Prof. Legesse Kassa Debusho. Her research focuses on BN models for analyzing correlated data, including multilevel and longitudinal data (https://orcid.org/0000-0001-5673-8037). She was a research visitor at King Abdullah University of Science and Technology, collaborating with Prof. Janet Van Niekerk and Prof. Håvard Rue. She is a recipient of the L’Oréal UNESCO For Women in Science Sub-Saharan Africa Award and a Schlumberger Foundation Faculty for the Future Fellowship.