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Disease Mapping With Winbugs And Mlwin


Disease Mapping With Winbugs And Mlwin
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Disease Mapping With Winbugs And Mlwin


Disease Mapping With Winbugs And Mlwin
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Author : Andrew B. Lawson
language : en
Publisher: John Wiley & Sons
Release Date : 2003-10-31

Disease Mapping With Winbugs And Mlwin written by Andrew B. Lawson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-31 with Mathematics categories.


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. Provides an introduction to Bayesian and multilevel modelling in disease mapping. Adopts a practical approach, with many detailed worked examples. Includes introductory material on WinBUGS and MLwiN. Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis. Suitable for public health workers and epidemiologists with a sound statistical knowledge. Supported by a Website featuring data sets and WinBUGS and MLwiN programs. 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.



Disease Mapping


Disease Mapping
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Author : Miguel A. Martinez-Beneito
language : en
Publisher: CRC Press
Release Date : 2019-07-02

Disease Mapping written by Miguel A. Martinez-Beneito and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-02 with Mathematics categories.


Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period, disease, etc. Although theory will be covered, the applied component will be equally as important with lots of practical examples offered. Features: Discusses the very latest developments on multivariate and multidimensional mapping. Gives a single state-of-the-art framework that unifies most of the previously proposed disease mapping approaches. Balances epidemiological and statistical points-of-view. Requires no previous knowledge of disease mapping. Includes practical sessions at the end of each chapter with WinBUGs/INLA and real world datasets. Supplies R code for the examples in the book so that they can be reproduced by the reader. About the Authors: Miguel A. Martinez Beneito has spent his whole career working as a statistician for public health services, first at the epidemiology unit of the Valencia (Spain) regional health administration and later as a researcher at the public health division of FISABIO, a regional bio-sanitary research center. He has been also the Bayesian Hierarchical Models professor for several seasons at the University of Valencia Biostatics Master. Paloma Botella Rocamora has spent most of her professional career in academia although she now works as a statistician for the epidemiology unit of the Valencia regional health administration. Most of her research has been devoted to developing and applying disease mapping models to real data, although her work as a statistician in an epidemiology unit makes her develop and apply statistical methods to health data, in general.



Bayesian Disease Mapping


Bayesian Disease Mapping
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Author : Andrew B. Lawson
language : en
Publisher: CRC Press
Release Date : 2008-08-05

Bayesian Disease Mapping written by Andrew B. Lawson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-05 with Mathematics categories.


Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. The book explores a range of topics in Bayesian inference and



Statistical Methods In Spatial Epidemiology


Statistical Methods In Spatial Epidemiology
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Author : Andrew B. Lawson
language : en
Publisher: John Wiley & Sons
Release Date : 2013-07-08

Statistical Methods In Spatial Epidemiology written by Andrew B. Lawson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-08 with Medical categories.


Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as disease mapping, ecological analysis, disease clustering, bio-terrorism, space-time analysis, surveillance and infectious disease modelling. Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques. This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.



Spatial And Syndromic Surveillance For Public Health


Spatial And Syndromic Surveillance For Public Health
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Author : Andrew B. Lawson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-05-13

Spatial And Syndromic Surveillance For Public Health written by Andrew B. Lawson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-13 with Medical categories.


Following the events of 9/11 and in the current world climate, there is increasing concern of the impact of potential bioterrorism attacks. Spatial surveillance systems are used to detect changes in public health data, and alert us to possible outbreaks of disease, either from natural resources or from bioterrorism attacks. Statistical methods play a key role in spatial surveillance, as they are used to identify changes in data, and build models of that data in order to make predictions about future activity. This book is the first to provide an overview of all the current key methods in spatial surveillance, and present them in an accessible form, suitable for the public health professional. It features an abundance of examples using real data, highlighting the practical application of the methodology. It is edited and authored by leading researchers and practitioners in spatial surveillance methods. Provides an overview of the current key methods in spatial surveillance of public health data. Includes coverage of both single and multiple disease surveillance. Covers all of the key topics, including syndromic surveillance, spatial cluster detection, and Bayesian data mining.



Multilevel Modelling For Public Health And Health Services Research


Multilevel Modelling For Public Health And Health Services Research
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Author : Alastair H. Leyland
language : en
Publisher: Springer Nature
Release Date : 2020-02-28

Multilevel Modelling For Public Health And Health Services Research written by Alastair H. Leyland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-28 with Medical categories.


This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download – not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets. The book’s practical review of MLA comprises: Theoretical, conceptual, and methodological background Statistical background The modelling process and presentation of research Tutorials with example datasets Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis. “Leyland and Groenewegen’s wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis.” ̶ Juan Merlo, Professor of Social Epidemiology, Lund University “Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health”. ̶ S. (Subu) V. Subramanian, Professor of Population Health and Geography, Harvard University



Handbook Of Spatial Epidemiology


Handbook Of Spatial Epidemiology
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Author : Andrew B. Lawson
language : en
Publisher: CRC Press
Release Date : 2016-04-06

Handbook Of Spatial Epidemiology written by Andrew B. Lawson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-06 with Mathematics categories.


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 imp



Quality Of Life Outcomes In Clinical Trials And Health Care Evaluation


Quality Of Life Outcomes In Clinical Trials And Health Care Evaluation
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Author : Stephen J. Walters
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-10

Quality Of Life Outcomes In Clinical Trials And Health Care Evaluation written by Stephen J. Walters and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-10 with Medical categories.


An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials. Quality of Life (QoL) outcomes or Person/Patient Reported Outcome Measures (PROMs) are now frequently being used in randomised controlled trials (RCTs) and observational studies. This book provides a practical guide to the design, analysis and interpretation of studies that use such outcomes. QoL outcomes tend to generate data with discrete, bounded and skewed distributions. Many investigators are concerned about the appropriateness of using standard statistical methods to analyse QoL data and want guidance on what methods to use. QoL outcomes are frequently used in cross-sectional surveys and non-randomised health-care evaluations. Provides a user-friendly guide to the design and analysis of clinical trials and observational studies in relation to QoL outcomes. Discusses the problems caused by QoL outcomes and presents intervention options to help tackle them. Guides the reader step-by-step through the selection of appropriate QoLs. Features exercises and solutions and a supporting website providing downloadable data files. Illustrated throughout with examples and case studies drawn from the author’s experience, this book offers statisticians and clinicians guidance on choosing between the numerous available QoL instruments.



Multiple Imputation And Its Application


Multiple Imputation And Its Application
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Author : James Carpenter
language : en
Publisher: John Wiley & Sons
Release Date : 2012-12-19

Multiple Imputation And Its Application written by James Carpenter and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-19 with Medical categories.


A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.



Statistics And The Evaluation Of Evidence For Forensic Scientists


Statistics And The Evaluation Of Evidence For Forensic Scientists
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Author : Colin Aitken
language : en
Publisher: John Wiley & Sons
Release Date : 2020-11-24

Statistics And The Evaluation Of Evidence For Forensic Scientists written by Colin Aitken and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-24 with Mathematics categories.


Statistics and the Evaluation of Evidence for Forensic Scientists The leading resource in the statistical evaluation and interpretation of forensic evidence The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That’s why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It’s written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. Discusses the entire chain of reasoning–from evidence pre-assessment to court presentation; Includes material for the understanding of evidence interpretation for single and multiple trace evidence; Provides real examples and data for improved understanding. Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.