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Description: |
xvii, 378 pages : illustrations, maps ; 25 cm. |
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Bibliography Note: |
Includes bibliographical references and index. |
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Contents Note: |
Contents: Bayesian inference and modeling -- Computational issues -- Residuals and goodness-of-fit -- Disease map reconstruction and relative risk estimation -- Disease cluster detection -- Regression and ecological analysis -- Putative hazard modeling -- Multiple scale analysis -- Multivariate disease analysis -- Spatial survival and longitudinal analysis -- Spatiotemporal disease mapping -- Disease map surveillance. |
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Summary, Etc. Note: |
Subject: Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. A biostatistics professor and WHO advisor, the author illustrates the use of Bayesian hierarchical modeling in the geographical analysis of disease through a range of real-world datasets. |
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Series Added Entry: |
Interdisciplinary statistics. |