Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests

ArXi:2508.14936v2 Announce Type: replace-cross Synthetic data holds substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns. However, many current methods suffer from limited quality, high computational demands, and complexity for non-experts. Furthermore, common evaluation strategies for synthetic data often fail to directly reflect statistical utility and measure privacy risks sufficiently.