9780295991849 - an integrative metaregression framework for descriptive epidemiology (publications on global health) (4 Ergebnisse)
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Zustand: New. First book-length treatment of model-based meta-analytic methods for descriptive epidemiology Editor(s): Flaxman, Abraham. Series: Publications on Global Health, Institute for Health Metrics and Evaluation. Num Pages: 600 pages, black & white illustrations. BIC Classification: MBNS. Category: (P) Professional & Voc…ational. Dimension: 263 x 186 x 22. Weight in Grams: 646. . 2015. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
An Integrative Metaregression Framework for Descriptive Epidemiology
Abraham D. Flaxman, Theo Vos, Christopher J. L. Murray, editors
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Hardcover. Zustand: Good. THERE ARE NO TARIFFS OR CUSTOMS DUTIES ON BOOKS. Book in good condition. Pages clean, tight and unmarked. Cover also in good condition, with only very minor spine creasing and scuffing. To provide the tools and knowledge needed in efforts to improve the health of the world's populations, researchers col…laborated on the Global Burden of Diseases, Injuries, and Risk Factors Study 2010. The study produced comprehensive estimates of more than 200 diseases and health risk factors in 187 countries over two decades, results that will be used by governments and non-governmental agencies to inform priorities for global health research, policies, and funding. An Integrative Metaregression Framework for Descriptive Epidemiology is the first book-length treatment of model-based meta-analytic methods for descriptive epidemiology used in the Global Burden of Disease Study 2010. In addition to collecting the prior work on compartmental modeling of disease, this book significantly extends the model by formally connecting the system dynamics model of disease progression to a statistical model of epidemiological rates and demonstrates how the two models were combined to allow researchers to integrate all available relevant data. Practical applications of the model to meta-analysis of several different diseases complement the theoretical foundations of what the editors call the integrative systems modeling of disease in populations. The book concludes with a detailed description of the future directions for research in model-based meta-analysis of descriptive epidemiological data.
