By Andrew B. Lawson
Since the booklet of the 1st variation, many new Bayesian instruments and techniques were constructed for space-time facts research, the predictive modeling of future health results, and different spatial biostatistical components. Exploring those new advancements, Bayesian ailment Mapping: Hierarchical Modeling in Spatial Epidemiology, moment Edition offers an up to date, cohesive account of the total diversity of Bayesian affliction mapping tools and purposes. A biostatistics professor and WHO consultant, the writer illustrates using Bayesian hierarchical modeling within the geographical research of illness via a number real-world datasets.
New to the second one Edition
- Three new chapters on regression and ecological research, putative risk modeling, and sickness map surveillance
- Expanded fabric on case occasion modeling and spatiotemporal analysis
- New and up-to-date examples
- Two new appendices that includes examples of built-in nested Laplace approximation (INLA) and conditional autoregressive (CAR) models
In addition to those new subject matters, the booklet covers extra traditional components akin to relative possibility estimation, clustering, spatial survival research, and longitudinal research. After an creation to Bayesian inference, computation, and version overview, the textual content specializes in very important issues, together with sickness map reconstruction, cluster detection, regression and ecological research, putative probability modeling, research of a number of scales and a number of ailments, spatial survival and longitudinal reports, spatiotemporal tools, and map surveillance. It exhibits how Bayesian disorder mapping can yield major insights into georeferenced future health info. WinBUGS and R are used all through for info manipulation and simulation.
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Extra resources for Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)
Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics) by Andrew B. Lawson