A Bayesian hierarchical model is a statistical model that represents data at multiple levels of abstraction, allowing for the incorporation of different sources of variability and uncertainty. This type of model is particularly useful for analyzing complex data structures where observations are grouped in natural ways, such as patients within hospitals or students within schools. By utilizing a hierarchical structure, these models enable sharing of information across groups, improving estimates and predictions while formally incorporating prior beliefs through Bayesian inference.
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