A comparison of Bayesian spatial models for disease mapping

DOI10.1191/0962280205sm388oazbMath1057.62097OpenAlexW2073222618WikidataQ36029681 ScholiaQ36029681MaRDI QIDQ4662795

Andrew Thomson, Sylvia Richardson, Nicky G. Best

Publication date: 30 March 2005

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1191/0962280205sm388oa

zbMATH Keywords

semi-parametric modelsmoving average modelsconditionally specified modelscorrelated normal priorsMarkov random fields models

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

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Cites Work

• Unnamed Item
• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Space-varying regression models: specifications and simulation
• Multi-dimensional multivariate Gaussian Markov random fields with application to image processing
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Bayesian Partitioning for Estimating Disease Risk
• Hierarchical Bayesian Modeling of Spatially Correlated Health Service Outcome and Utilization Rates
• Model-Based Geostatistics
• Posterior distribution of hierarchical models using CAR(1) distributions
• Modeling Spatial Variation in Disease Risk
• Hidden Markov Models and Disease Mapping
• Towards joint disease mapping
• Bayesian Detection of Clusters and Discontinuities in Disease Maps
• Bayesian Detection and Modeling of Spatial Disease Clustering
• Bayesian Measures of Model Complexity and Fit
• A Review of Methods for the Statistical Analysis of Spatial Patterns of Disease
• A Shared Component Model for Detecting Joint and Selective Clustering of Two Diseases
• Proper multivariate conditional autoregressive models for spatial data analysis

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