Knowing the contents of this chapter which introduce the concept of hierarchical model and its famous application, eight school model, itself is helpful enough!
5.1 Constructing a parameterized prior distribution
5.2 Exchangeability and setting up hierarchical models
5.3 Fully Bayesian analysis of conjugate hierarchical models
5.4 Estimating exchangeable parameters from a normal models
5.5 Example: parallel experiments in eight schools
5.6 Hierarchical modeling applied to a meta-analysis
5.7 Weakly informative priors for hierarchical variance parameters
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