Hierarchical models are advantageous for several reasons:
1. Handling Nested Data: They appropriately manage data that have a nested structure, which is common in epidemiological studies. For example, data from patients could be nested within hospitals, and hospitals within regions. 2. Reducing Bias: By considering the hierarchical structure of the data, these models reduce the potential for biased estimates that can result from ignoring such structures. 3. Understanding Variability: They help in understanding the variability at different levels, such as individual versus group-level variations.
