APPLIED BAYESIAN HIERARCHICAL METHODS

Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling instructions, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of models with random effects. The text focuses on applications in the health and social sciences, particularly spatial and clinical epidemiology, political science, and econometrics; covers such topics as Bayesian factor analysis; and includes a range of worked examples in WinBUGS, BayesX, and MLWin. The author demonstrates not only the flexibility of Bayesian techniques but also the rigor that can be obtained by using Bayesian model checking techniques.