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Bayesian Disease Mapping

Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling;

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Bayesian Disease Mapping

predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping;

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Bayesian Disease Mapping

predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping;

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Disease Mapping with WinBUGS and MLwiN

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include;

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Disease Mapping

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced;

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Disease Mapping

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Bayesian Methods in Epidemiology

Written by a biostatistics expert with over 20 years of experience in the field, Bayesian Methods in Epidemiology presents statistical;

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Bayesian Methods in Epidemiology

Written by a biostatistics expert with over 20 years of experience in the field, Bayesian Methods in Epidemiology presents statistical;

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Modern Spatiotemporal Geostatistics

Scholarly introductory treatment explores the role of modern geostatistics in improved mathematical models of scientific mapping;

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T1-Mapping in Myocardial Disease

allowed an unprecedented opportunity to elucidate the pathology, diagnosis and prognosis of cardiovascular disease. T1-Mapping;

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Genetic Mapping of Disease Genes

A state-of-the-art reference, Genetic Mapping of Disease Genes presents a detailed account of the new methodical approaches to gene mapping;

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Disease Modelling and Public Health, Part A

of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality;

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Cartographies of Disease

Cartographies of Disease: Maps, Mapping, and Medicine is a comprehensive survey of the technology of mapping and its relationship to the;

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Disease Mapping And Risk Assessment For Public Health

evaluation of disease mapping and risk assessment. It includes a broad variety of statistical techniques and where appropriate, examples are included;

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An Introductory Guide To Disease Mapping

role of disease mapping within epidemiology, highlighting its important role in studies of environmental health and environmental epidemiology;

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Bayesian Analysis of Infectious Diseases

Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary;

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Statistical Methods for QTL Mapping

comprehensive coverage of Bayesian models and MCMC algorithms and describes methods for multi-trait QTL mapping and eQTL mapping, including meta-trait;

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Mapping Disease Transmission Risk - Enriching Models Using Biogeography and Ecology

infectious disease mapping methods. His work - the culmination of twelve years of refinement - breaks new ground by integrating biogeographic and;

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Handbook of Spatial Epidemiology

. The second part presents basic statistical methods used in spatial epidemiology, including fundamental likelihood principles, Bayesian methods;

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Bayesian Methods For Data Analysis

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the;

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Functional Connectivity, An Issue of Neuroimaging Clinics of North America

include: Applications of rs-fMRI to presurgical mapping: sensorimotor mapping; Dynamic functional connectivity methods; Machine learning;

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Bayesian Adaptive Methods for Clinical Trials

Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a;

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Spatial Epidemiological Approaches in Disease Mapping and Analysis

Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips;

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Spatial Epidemiological Approaches in Disease Mapping and Analysis

Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips;

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