{"product_id":"disease-mapping-with-winbugs-and-mlwin-hardcover","title":"Disease Mapping with Winbugs and Mlwin - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAndrew B. Lawson\u003c\/b\u003e (Author), \u003cb\u003eWilliam J. Browne\u003c\/b\u003e (Author), \u003cb\u003eCarmen L. Vidal Rodeiro\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eDisease 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. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eProvides an introduction to Bayesian and multilevel modelling in disease mapping.\u003c\/li\u003e \u003cli\u003eAdopts a practical approach, with many detailed worked examples.\u003c\/li\u003e \u003cli\u003eIncludes introductory material on WinBUGS and MLwiN.\u003c\/li\u003e \u003cli\u003eDiscusses three applications in detail - relative risk estimation, focused clustering, and ecological analysis.\u003c\/li\u003e \u003cli\u003eSuitable for public health workers and epidemiologists with a sound statistical knowledge.\u003c\/li\u003e \u003cli\u003eSupported by a Website featuring data sets and WinBUGS and MLwiN programs.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eDisease Mapping with WinBUGS and MLwiN\u003c\/i\u003e 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.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eDisease 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. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eProvides an introduction to Bayesian and multilevel modelling in disease mapping.\u003c\/li\u003e \u003cli\u003eAdopts a practical approach, with many detailed worked examples.\u003c\/li\u003e \u003cli\u003eIncludes introductory material on WinBUGS and MLwiN.\u003c\/li\u003e \u003cli\u003eDiscusses three applications in detail ? relative risk estimation, focused clustering, and ecological analysis.\u003c\/li\u003e \u003cli\u003eSuitable for public health workers and epidemiologists with a sound statistical knowledge.\u003c\/li\u003e \u003cli\u003eSupported by a Website featuring data sets and WinBUGS and MLwiN programs.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eDisease Mapping with WinBUGS and MLwiN\u003c\/i\u003e 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.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eAndrew 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.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 292\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.81 x 9.22 x 5.98 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 12, 2003\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47337183215865,"sku":"9780470856048","price":195.77,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/5mBIPGWJnk9780470856048.webp?v=1769675449","url":"https:\/\/bookscloud.io\/products\/disease-mapping-with-winbugs-and-mlwin-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}