Disease Mapping with Winbugs and Mlwin
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Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages ? such as WinBUGS and MLwiN ? are now easy to implement in practice. * Provides an introduction to Bayesian and multilevel modelling in disease mappin...
Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages ? such as WinBUGS and MLwiN ? are now easy to implement in practice. * Provides an introduction to Bayesian and multilevel modelling in disease mapping. * Adopts a practical approach, with many detailed worked examples. * Includes introductory material on WinBUGS and MLwiN. * Discusses three applications in detail ? relative risk estimation, focused clustering, and ecological analysis. * Suitable for public health workers and epidemiologists with a sound statistical knowledge. * Supported by a Website featuring data sets and WinBUGS and MLwiN programs. Disease Mapping with WinBUGS and MLwiN provides a practical introduction to the use of software for disease mapping for researchers, practitioners and graduate students from statistics, public health and epidemiology who analyse disease incidence data.
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