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Produktbild: Bayesian Disease Mapping
Band 20

Bayesian Disease Mapping

Aus der Reihe Interdisciplinary Statistics

Fr. 105.00

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Beschreibung

In line with the recent growth of Bayesian methods applied to the modeling of geo-referenced health data, Bayesian Disease Mapping presents a practical overview of Bayesian modeling and computation in disease mapping. It covers various application areas, including disease map reconstruction, disease...

Beschreibung

In line with the recent growth of Bayesian methods applied to the modeling of geo-referenced health data, Bayesian Disease Mapping presents a practical overview of Bayesian modeling and computation in disease mapping. It covers various application areas, including disease map reconstruction, disease cluster detection, multi-scale disease mapping, spatio-temporal models, spatial survival analysis, spatial longitudinal analysis, and latent structure models. The book features a wide range of detailed case studies to illustrate how the methods can be applied. The author implements all examples using R and WinBUGS and provides additional code and datasets available for download on the web.

Produktdetails

Einband

Gebundene Ausgabe
Erscheinungsdatum

01.08.2008
Verlag Chapman And Hall
Seitenzahl

362

Produktdetails

Einband

Gebundene Ausgabe
Erscheinungsdatum

01.08.2008
Verlag Chapman And Hall
Seitenzahl

362
Maße (L/B/H)

23.6/15.7/2.3 cm
Gewicht

635 g
Sprache

Englisch
ISBN

978-1-58488-840-6

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  • Produktbild: Bayesian Disease Mapping
  • BACKGROUND Introduction Data Sets Bayesian Inference and Modeling Likelihood Models Prior Distributions Posterior Distributions Predictive Distributions Bayesian Hierarchical Modeling Hierarchical Models Posterior Inference Exercises Computational Issues Posterior Sampling Markov Chain Monte Carlo Methods Metropolis and Metropolis-Hastings Algorithms Gibbs Sampling Perfect Sampling Posterior and Likelihood Approximations Exercises Residuals and Goodness-of-Fit Model Goodness-of-Fit Measures General Residuals Bayesian Residuals Predictive Residuals and the Bootstrap Interpretation of Residuals in a Bayesian Setting Exceedence Probabilities Exercises THEMES Disease Map Reconstruction and Relative Risk Estimation An Introduction to Case Event and Count Likelihoods Specification of the Predictor in Case Event and Count Models Simple Case and Count Data Models with Uncorrelated Random Effects Correlated Heterogeneity Models Convolution Models Model Comparison and Goodness-of-Fit Diagnostics Alternative Risk Models Edge Effects Exercises Disease Cluster Detection Cluster Definitions Cluster Detection using Residuals Cluster Detection using Posterior Measures Cluster Models Edge Detection and Wombling Ecological Analysis General Case of Regression Biases and Misclassification Error Putative Hazard Models Multiple Scale Analysis Modifiable Areal Unit Problem (MAUP) Misaligned Data Problem (MIDP) Multivariate Disease Analysis Notation for Multivariate Analysis Two Diseases Multiple Diseases Spatial Survival and Longitudinal Analyses General Issues Spatial Survival Analysis Spatial Longitudinal Analysis Extensions to Repeated Events Spatiotemporal Disease Mapping Case Event Data Count Data Alternative Models Infectious Diseases Appendix A: Basic R and WinBUGS Appendix B: Selected WinBUGS Code Appendix C: R Code for Thematic Mapping References Index