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Bayesian Disease Mapping

Bayesian Disease Mapping Author Andrew B. Lawson
ISBN-10 9781351271745
Release 2018-05-20
Pages 464
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Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.



Handbook of Spatial Epidemiology

Handbook of Spatial Epidemiology Author Andrew B. Lawson
ISBN-10 9781482253023
Release 2016-04-06
Pages 686
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Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space–time variations in disease incidences. These analyses can provide important information that leads to better decision making in public health. The first part of the book addresses general issues related to epidemiology, GIS, environmental studies, clustering, and ecological analysis. The second part presents basic statistical methods used in spatial epidemiology, including fundamental likelihood principles, Bayesian methods, and testing and nonparametric approaches. With a focus on special methods, the third part describes geostatistical models, splines, quantile regression, focused clustering, mixtures, multivariate methods, and much more. The final part examines special problems and application areas, such as residential history analysis, segregation, health services research, health surveys, infectious disease, veterinary topics, and health surveillance and clustering. Spatial epidemiology, also known as disease mapping, studies the geographical or spatial distribution of health outcomes. This handbook offers a wide-ranging overview of state-of-the-art approaches to determine the relationships between health and various risk factors, empowering researchers and policy makers to tackle public health problems.



Spatial Point Patterns

Spatial Point Patterns Author Adrian Baddeley
ISBN-10 9781482210217
Release 2015-11-11
Pages 810
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Modern Statistical Methodology and Software for Analyzing Spatial Point Patterns Spatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software development experiences, methodological research, and broad scientific collaborations to deliver a book that clearly and succinctly explains concepts and addresses real scientific questions. Practical Advice on Data Analysis and Guidance on the Validity and Applicability of Methods The first part of the book gives an introduction to R software, advice about collecting data, information about handling and manipulating data, and an accessible introduction to the basic concepts of point processes. The second part presents tools for exploratory data analysis, including non-parametric estimation of intensity, correlation, and spacing properties. The third part discusses model-fitting and statistical inference for point patterns. The final part describes point patterns with additional "structure," such as complicated marks, space-time observations, three- and higher-dimensional spaces, replicated observations, and point patterns constrained to a network of lines. Easily Analyze Your Own Data Throughout the book, the authors use their spatstat package, which is free, open-source code written in the R language. This package provides a wide range of capabilities for spatial point pattern data, from basic data handling to advanced analytic tools. The book focuses on practical needs from the user’s perspective, offering answers to the most frequently asked questions in each chapter.



Bayesian Analysis for Population Ecology

Bayesian Analysis for Population Ecology Author Ruth King
ISBN-10 UOM:39015084177651
Release 2009-09-15
Pages 442
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Modern Bayesian methods have an important role to play in population ecology. Statistical methods for the analysis of mark-recapture-recovery data on wild animals continue to develop in response to the availability of long-term data sets and advances in animal marking and tracking techniques. Bringing together top experts in the field, this book presents up-to-date Bayesian procedures in an accessible manner, illustrated by a wide range of real examples and complemented by accessible computer programs. The authors include WinBUGS and R code for all of the analyses that are performed in the text.



The British National Bibliography

The British National Bibliography Author Arthur James Wells
ISBN-10 STANFORD:36105211722686
Release 2009
Pages
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The British National Bibliography has been writing in one form or another for most of life. You can find so many inspiration from The British National Bibliography also informative, and entertaining. Click DOWNLOAD or Read Online button to get full The British National Bibliography book for free.