Hierarchical Bayesian Modeling of Spatially Correlated Health Service Outcome and Utilization Rates

DOI10.1111/1541-0420.00037zbMath1210.62028OpenAlexW2003054692WikidataQ52010737 ScholiaQ52010737MaRDI QIDQ3079112

Ying C. MacNab

Publication date: 1 March 2011

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1541-0420.00037

zbMATH Keywords

Markov chain Monte Carlorandom effectsdisease mappingconditional autoregressive priorshealth services researchBayesian hierarchical spatial modelintraventricular hemorrhage incidence

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Medical applications (general) (92C50) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (10)

Bayesian spatial quantile regression for areal count data, with application on substitute care placements in Texas ⋮ Estimation in Bayesian Disease Mapping ⋮ Rejoinder on: ``Some recent work on multivariate Gaussian Markov random fields ⋮ Detection of Significant Disease Risks Using a Spatial Conditional Autoregressive Model ⋮ Empirical Bayes and fully Bayes procedures to detect high-risk areas in disease mapping ⋮ On empirical Bayes penalized quasi-likelihood inference in GLMMs and in Bayesian disease mapping and ecological modeling ⋮ Smooth-CAR mixed models for spatial count data ⋮ A comparison of Bayesian spatial models for disease mapping ⋮ Conservative prior distributions for variance parameters in hierarchical models ⋮ Modelling risks in disease mapping

Cites Work

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• Bayesian image restoration, with two applications in spatial statistics (with discussion)
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• Large Hierarchical Bayesian Analysis of Multivariate Survival Data
• Bayesian Measures of Model Complexity and Fit
• Monte Carlo sampling methods using Markov chains and their applications

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