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.
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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Andrew B. Lawson is a professor of biostatistics and eminent scholar in the Division of Biostatistics and Epidemiology in the College of Medicine at the Medical University of South Carolina. He is an ASA fellow and an advisor in disease mapping and risk assessment for the World Health Organization. Dr. Lawson has published over 100 journal papers and eight books and is the founding editor of Spatial and Spatio-temporal Epidemiology. He received a PhD in spatial statistics from the University of St. Andrews. His research interests include the analysis of clustered disease maps, spatial and spatio-temporal disease surveillance, nutritional measurement error, and Bayesian latent variable and SEM modeling.
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Vendeur : Fox and Tome Booksellers, Frederick, MD, Etats-Unis
Hardback. Etat : Good. Ex Library book and has stickers or markings as such. No writing or markings other then from the library, All pages intact and clean, shows minor signs of wear from use. Great reading copy, Save money and recycle books! Shipped with care in a bubble mailer. --- This volume offers a practical guide to applying Bayesian hierarchical and multilevel statistical methods to the study of geographically referenced disease incidence data, with worked examples implemented in the WinBUGS and MLwiN software packages. Lawson, Browne, and Vidal Rodeiro address common applications including disease cluster detection, ecological regression, and health resource planning, presenting techniques accessible to epidemiologists and public health researchers. Part of Wiley's Statistics in Practice series, the book bridges the gap between theoretical spatial epidemiology and the computational tools needed to fit complex models to real-world data. Ex-Library. N° de réf. du vendeur RP-250619-shelf-79-006
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