Modern Statistical Methods in Chronic Disease Epidemiology PDF Download

Author: Suresh H. Moolgavkar
Publisher:
ISBN:
Category :
Languages : en
Pages : 282

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Author: Suresh H. Moolgavkar
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Yu-Kang Tu
Publisher: Springer Science & Business Media
ISBN: 9400730241
Category : Medical
Languages : en
Pages : 315

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Book Description
Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.

Author: Ray M. Merrill
Publisher: Jones & Bartlett Publishers
ISBN: 1284034437
Category : Epidemiology
Languages : en
Pages : 944

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Covers all the core topics, such as digital logic, data representation, machine-level language, general organization, and much more.

Author: Niel Hens
Publisher: Springer Science & Business Media
ISBN: 1461440726
Category : Medical
Languages : en
Pages : 300

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Book Description
Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology. It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.

Author: Toshiro Tango
Publisher: Springer Science & Business Media
ISBN: 1441915729
Category : Mathematics
Languages : en
Pages : 240

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This book is intended to provide a text on statistical methods for detecting clus ters and/or clustering of health events that is of interest to ?nal year undergraduate and graduate level statistics, biostatistics, epidemiology, and geography students but will also be of relevance to public health practitioners, statisticians, biostatisticians, epidemiologists, medical geographers, human geographers, environmental scien tists, and ecologists. Prerequisites are introductory biostatistics and epidemiology courses. With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Further more, the research area of statistical tests for disease clustering now attracts a wide audience due to the perceived need to implement wide ranging monitoring systems to detect possible health related bioterrorism activity. With this background and the development of the geographical information system (GIS), the analysis of disease clustering of health events has seen considerable development over the last decade. Therefore, several excellent books on spatial epidemiology and statistics have re cently been published. However, it seems to me that there is no other book solely focusing on statistical methods for disease clustering. I hope that readers will ?nd this book useful and interesting as an introduction to the subject.

Author: Suresh H. Moolgavkar
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 312

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Proceedings of a conference sponsored by the SIAM Institute for Mathematics and Society, and supported by the Department of Energy. Brings together recent developments in the statistical methodology for chronic disease epidimiology. The contributors are all at the forefront of biostatistics research.

Author: Ron Brookmeyer
Publisher: Oxford University Press
ISBN: 0199748977
Category : Medical
Languages : en
Pages : 389

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Public health faces critical challenges ranging from outbreaks of new and old pathogens to the threat of bioterrorism and the impact of lifestyle and environmental changes on health. Modern tools of health surveillance and sound statistical practices are essential for meeting these challenges and providing accurate warnings about real public health threats without wasting resources on false alarms. Advances in statistical techniques, computing power and the Internet have led to many new approaches to monitoring population health, analyzing the data, and rapidly sharing it. This text explores the critical issues in the statistical analysis and interpretation of public health surveillance data. It covers statistical methods for detecting disease outbreaks and clusters, the use of survey methods, interpreting time trends and geographic patterns, exploratory statistical analysis of surveillance data, and web-based health reporting systems for the rapid detection of public health problems, among other topics. The methodological approaches are illustrated in discussions of several current public health issues, including the HIV/AIDS epidemic, anthrax, health effects of particulate air pollution, and trends in prostate cancer. The methods are broadly applicable to surveillance systems and registries for numerous health conditions, e.g. infectious diseases, chronic diseases, adverse drug reactions. The book provides numerous illustrations, worked examples, and practical information for actually implementing the methods. It will serve as a reference for public health practitioners and as a textbook for courses on disease surveillance taken by students of statistics biostatistics, epidemiology or public health.

Author: Ørnulf Borgan
Publisher: CRC Press
ISBN: 1351650122
Category : Mathematics
Languages : en
Pages : 700

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Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ørnulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.

Author: Leonhard Held
Publisher: CRC Press
ISBN: 9781032087351
Category : Communicable diseases
Languages : en
Pages : 554

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Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material