Hierarchical models, also known as multi-level models or mixed-effects models, are statistical models that account for data that is nested or grouped at more than one level. In epidemiology, hierarchical models are particularly useful for analyzing complex data structures where observations are grouped into clusters, such as patients within hospitals or individuals within geographic regions.
