Malgorzata Roos' project: “SEDA: Sensitivity diagnostics for Bayesian hierarchical models” was recently awarded funding from the Swiss National Science Foundation.
This project is a close collaboration between working groups based in Saudi Arabia, France and the EBPI Switzerland.
Bayesian hierarchical models (BHMs) are a well-established statistical methodology. They can be conveniently estimated by Bayesian general-purpose software systems. In particular, Stan, JAGS and R-INLA represent the current state-of-the-art for fitting BHMs to complex hierarchical data. Although BHMs are very useful in practice, the reliability of their inference is subject to several model assumptions. The project will focus on methodological research and on the development of sensitivity diagnostics for BHMs.
Congratulations, Malgorzata, upon your first SNSF funding!