Search results for: statistical-methods-in-epidemiology

Statistical Methods in Epidemiologic Research

Author : Ray M. Merrill
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Statistical Methods in Epidemiology

Author : Harold A. Kahn
File Size : 23.32 MB
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Based on Kahn's An Introduction to Epidemiological Methods (Oxford, 1983), this book contains a wealth of new material, including a substantially expanded discussion of the statistical concepts and methods fundamental to epidemiology.

Statistical Methods in Genetic Epidemiology

Author : Duncan C. Thomas
File Size : 65.77 MB
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This balanced and well-integrated text gives a lucid overview of the entire process of genetic epidemiology, from familial aggregation through segregation, likage, and association studies. It is illustrated throughout with examples from the literature on cancer genetics. Statistical concepts are developed in depth, but with a focus on applications. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics are included. Oriented to graduate students in biostatistics, epidemiology, and human genetics, the book will also be a useful reference for researchers. It gives equal emphasis to study designs and data analysis.

Statistical Methods for Environmental Epidemiology with R

Author : Roger D. Peng
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As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These constraints typically lead to the development and use of more sophisticated (and pot- tially less transparent) statistical models and the integration of large hi- dimensional databases. New technologies and the widespread availability of powerful computing are also adding to the complexities of scienti c inves- gation by allowing researchers to t large numbers of models and search over many sets of variables. As the number of variables measured increases, so do the degrees of freedom for in uencing the association between a risk factor and an outcome of interest. We have written this book, in part, to describe our experiences developing and applying statistical methods for the estimation for air pollution health e ects. Our experience has convinced us that the application of modern s- tistical methodology in a reproducible manner can bring to bear subst- tial bene ts to policy-makers and scientists in this area. We believe that the methods described in this book are applicable to other areas of environmental epidemiology, particularly those areas involving spatial{temporal exposures.

Statistical Methods in Environmental Epidemiology

Author : Duncan C. Thomas
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Environmental epidemiology is the study of the environmental causes of disease in populations and how these risks vary in relation to intensity and duration of exposure and other factors like genetic susceptibility. As such, it is the basic science upon which governmental safety standards and compensation policies for environmental and occupational exposure are based. Profusely illustrated with examples from the epidemiologic literature on ionizing radiation and air pollution, thistext provides a systematic treatment of the statistical challenges that arise in environmental health studies and the use epidemiologic data in formulating public policy, at a level suitable for graduate students and epidemiologic researchers.After a general overview of study design and statistical methods for epidemiology generally, the book goes on to address the problems that are unique to environmental health studies, special-purpose designs like two-phase case-control studies and countermatching, statistical methods for modeling exposure-time-response relationships, longitudinal and time-series studies, spatial and ecologic methods, exposure measurement error, interactions, and mechanistic models. It also discusses studiesaimed at evaluating the public health benefits of interventions to improve the environment, the use of epidemiologic data to establish environmental safety standards and compensation policy, and concludes with emerging problems in reproductive epidemiology, natural and man-made disasters like globalwarming, and the global burden of environmentally caused disease. No other book provides such a broad perspective on the methodological challenges in this field at a level accessible to both epidemiologists and statisticians.

Statistical Models in Epidemiology

Author : David Clayton
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This self-contained account of the statistical basis of epidemiology has been written for those with a basic training in biology. No previous knowledge of the subject is assumed and mathematics is deliberately kept at a manageable level. Based on a highly successful course, this book explains the essential statistics for all epidemiologists.

Statistical Analysis of Epidemiologic Data

Author : Steve Selvin
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Analytic procedures suitable for the study of human disease are scattered throughout the statistical and epidemiologic literature. Explanations of their properties are frequently presented in mathematical and theoretical language. This well-established text gives readers a clear understanding of the statistical methods that are widely used in epidemiologic research without depending on advanced mathematical or statistical theory. By applying these methods to actual data, Selvin reveals the strengths and weaknesses of each analytic approach. He combines techniques from the fields of statistics, biostatistics, demography and epidemiology to present a comprehensive overview that does not require computational details of the statistical techniques described. For the Third Edition, Selvin took out some old material (e.g. the section on rarely used cross-over designs) and added new material (e.g. sections on frequently used contingency table analysis). Throughout the text he enriched existing discussions with new elements, including the analysis of multi-level categorical data and simple, intuitive arguments that exponential survival times cause the hazard function to be constant. He added a dozen new applied examples to illustrate such topics as the pitfalls of proportional mortality data, the analysis of matched pair categorical data, and the age-adjustment of mortality rates based on statistical models. The most important new feature is a chapter on Poisson regression analysis. This essential statistical tool permits the multivariable analysis of rates, probabilities and counts.

Modern Methods for Epidemiology

Author : Yu-Kang Tu
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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.

Statistical methods in epidemiology

Author : Joyce Almond
File Size : 62.99 MB
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Statistics in Epidemiology

Author : Hardeo Sahai
File Size : 80.57 MB
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Epidemiologic studies provide research strategies for investigating public health and scientific questions relating to the factors that cause and prevent ailments in human populations. Statistics in Epidemiology: Methods, Techniques and Applications presents a comprehensive review of the wide range of principles, methods and techniques underlying prospective, retrospective and cross-sectional approaches to epidemiologic studies. Written for epidemiologists and other researchers without extensive backgrounds in statistics, this new book provides a clear and concise description of the statistical tools used in epidemiology. Emphasis is given to the application of these statistical tools, and examples are provided to illustrate direct methods for applying common statistical techniques in order to obtain solutions to problems. Statistics in Epidemiology: Methods, Techniques and Applications goes beyond the elementary material found in basic epidemiology and biostatistics books and provides a detailed account of techniques:

Handbook of Statistical Methods for Case Control Studies

Author : Ørnulf Borgan
File Size : 70.59 MB
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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.

Modern Statistical Methods in Chronic Disease Epidemiology

Author : United States. Department of Energy
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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.

Statistical Methods for Global Health and Epidemiology

Author : Xinguang Chen
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This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health and epidemiology involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, cancer, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective; addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation.

Statistical Methods for Disease Clustering

Author : Toshiro Tango
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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.

Statistical Methods in Epidemiology

Author : Harold A. Kahn
File Size : 35.79 MB
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This book is an expanded version of the Kahn's widely used text, An Introduction to Epidemiologic Methods (Oxford, 1983). It provides clear insight into the basic statistical tools used in epidemiology and is written so that those without advanced statistical training can comprehend the ideas underlying the analytical techniques. The authors emphasize the extent to which similar results are obtained from different methods, both simple and complex. To this edition they have added a new chapter on "Comparison of Numerical Results for Various Methods of Adjustment" and also one on "The Primacy of Data Collection." New topics include the Kaplan-Meier product-limit method and the Cox proportional hazards model for analysis of time-related outcomes. An appendix of data from the Framingham Heart Study is used to illustrate the application of various analytical methods to an identical set of real data and provides source material for student exercises. The text has been updated throughout.

Epidemiological Research Methods

Author : Donald R. McNeil
File Size : 81.59 MB
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The concepts of epidemiology, the science that uses statistical methods to investigate associations between risk factors and disease outcomes in human populations, are developed using examples involving real data from published studies. The relevant statistical methods are developed systematically to provide an integrated approach to observational and experimental studies. After covering basic measurement, study design, and study credibility issues, the author continues with basic statistical methods and techniques for adjusting risk estimates for confounders. Statistical models including logistic regression and the proportional hazards model for survival analysis are explained in detail in the following chapters, concluding with an explanation of the general methods for determining the sample size and power requirements for an epidemiological study. Taking advantage of the power, accessibility and user-friendliness of modern computer packages, the author uses a variety of interesting data sets and graphical displays to illustrate the methods. Epidemiological Research Methods will be of interest to students and research workers who need to learn and appreciate modern approaches to the subject. Without unnecessary emphasis on mathematics or theory, the book will enable the reader to gain a greater level of understanding of the underlying methods than is normally provided in books on epidemiology.

A Statistical Approach to Genetic Epidemiology

Author : Andreas Ziegler
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This is the second edition of the successful textbook written by the prize-winning scientist Andreas Ziegler, former President of the German Chapter of the International Biometric Society, and Inke König, who has been teaching the subject over many years. The book gives a comprehensive introduction into the relevant statistical methods in genetic epidemiology. The second edition is thoroughly revised, partly rewritten and includes now chapters on segregation analysis, twin studies and estimation of heritability. The book is ideally suited for advanced students in epidemiology, genetics, statistics, bioinformatics and biomathematics. Like in the first edition the book contains many problems and solutions and it comes now optionally with an e-learning course created by Friedrich Pahlke. This e-learning course has been developed to complement the book. Both provide a unique support tool for teaching the subject.

Statistical Methods in Epidemiology

Author : David Clayton
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Quantitative Methods for Health Research

Author : Bruce
File Size : 44.45 MB
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A practical introduction to epidemiology, biostatistics, and research methodology for the whole health care community This comprehensive text, which has been extensively revised with new material and additional topics, utilizes a practical slant to introduce health professionals and students to epidemiology, biostatistics, and research methodology. It draws examples from a wide range of topics, covering all of the main contemporary health research methods, including survival analysis, Cox regression, and systematic reviews and meta-analysis—the explanation of which go beyond introductory concepts. This second edition of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics also helps develop critical skills that will prepare students to move on to more advanced and specialized methods. A clear distinction is made between knowledge and concepts that all students should ensure they understand, and those that can be pursued further by those who wish to do so. Self-assessment exercises throughout the text help students explore and reflect on their understanding. A program of practical exercises in SPSS (using a prepared data set) helps to consolidate the theory and develop skills and confidence in data handling, analysis, and interpretation. Highlights of the book include: Combining epidemiology and bio-statistics to demonstrate the relevance and strength of statistical methods Emphasis on the interpretation of statistics using examples from a variety of public health and health care situations to stress relevance and application Use of concepts related to examples of published research to show the application of methods and balance between ideals and the realities of research in practice Integration of practical data analysis exercises to develop skills and confidence Supplementation by a student companion website which provides guidance on data handling in SPSS and study data sets as referred to in the text Quantitative Methods for Health Research, Second Edition is a practical learning resource for students, practitioners and researchers in public health, health care and related disciplines, providing both a course book and a useful introductory reference.

Statistical Methods in Spatial Epidemiology

Author : Andrew B. Lawson
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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.