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9781032177151

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...The material covered in the almost 600 pages is broad, rich, and presented in a dense and conciseway. There is a notable emphasis on longitudinal models, spatial applications as well as structural equations models, which seems natural given the focus on hierarchicalmodels...The readership that will benefit most from the book might be statisticians with intermediateor advanced-level expertise in Bayesian statistics and at least some basic experience in the software implementation of Bayesian modeling techniques. The second edition is particularly worthwhile since it catches up with the computational developments of the last decade. Overall, the book nicely illustrates the richness and the flexibility of hierarchical modeling options within the Bayesian framework. - Christian Stock, Biometrical Journal, October 2020

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Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.

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