Integrating information from similar data sites when developing clinical prediction models for patients from a target site (A01)

• Subject Area: Mathematics ; Epidemiology and Medical Biometry/Statistics
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 499552394

The project will provide methodology based on weighting of similar data from external sites in a prediction model for a target site. We will investigate different strategies for quantifying similarity, including 1) propensity score-based approaches, 2) similarity quantified parametrically as well as nonparametrically via the difference between the conditional empirical distribution of the outcome given the covariates per site, and 3) a deep learning approach. Besides empirical evaluation, we will provide comprehensive mathematical theory on the parameter estimates of corresponding regression models.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1597: Small Data
• Applicant Institution: Albert-Ludwigs-Universität Freiburg
• Project Heads: Professorin Dr. Angelika Rohde; Dr. Daniela Zöller