Bayesian Hierarchical Models: With Applications Using R, Second Edition (Hardcover, 2)

Chapter 1 Bayesian Methods for Complex Data: Estimation and Inference; Chapter 2 Computing Options and Strategies; Chapter 3 Model Fit, Comparison, and Checking; Chapter 4 Borrowing Strength Estimation for Exchangeable Units; Chapter 5 Structured Priors Recognizing Similarity over Time and Space; Chapter 6 Regression Techniques using Hierarchical Priors; Chapter 7 Multilevel Models; Chapter 8 Regression for Causal Effects with Observational Data; Chapter 9 Hierarchical Models for Panel Data; Chapter 10 Multivariate Priors, with a Focus on Factor and Structural Equation Models; Chapter 11 Survival and Event History Models; Chapter 12 Hierarchical Methods for Nonlinear Regression.