Bayesian disease mapping; hierarchical modeling in spatial epidemiology.9781584888406 Bayesian disease mapping; hierarchical modeling in spatial epidemiology Spatial epidemiology is the study of the spatial distribution of disease. . Lawson, Andrew B. Chapman & Hall/CRC 2008 344 pages $79.95 Hardcover Chapman & Hall/CRC interdisciplinary statistics series RA792 Lawson (biostatistics, Medical U. of South Carolina South Carolina, state of the SE United States. It is bordered by North Carolina (N), the Atlantic Ocean (SE), and Georgia (SW). Facts and Figures Area, 31,055 sq mi (80,432 sq km). Pop. (2000) 4,012,012, a 15. ) explores Bayesian hierarchical modeling and its application to the geographical analysis of disease. He introduces Bayesian inference Bayesian inference is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. The name "Bayesian" comes from the frequent use of Bayes' theorem in the inference process. and modeling, then centers on computation, including Markov chain Monte Carlo Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods), are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. methods and Metropolis or Metropolis-Hastings algorithms, perfect sampling, posterior and likelihood approximations, residuals, and goodness-of-fit. He then applies these basic techniques to general themes, including disease map reconstruction and relative risk estimation, disease cluster detection, ecological analysis, multiple scale analysis, multivariant disease analysis, spatial survival and longitudinal analysis, and spatiotemporal spa·ti·o·tem·po·ral adj. 1. Of, relating to, or existing in both space and time. 2. Of or relating to space-time. [Latin spatium, space + temporal1. disease mapping. Lawson's appendices include information on basic R and WinBUGS code. ([c]20082005 Book News, Inc., Portland, OR) |
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