Bayesian methods provide a probabilistic approach to statistical inference, incorporating prior knowledge with current data. This is particularly useful in situations where data are scarce or uncertain. Bayesian hierarchical models can handle complex data structures and account for multiple levels of variability, making them suitable for multi-center studies.
