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Author: Harold A. Kahn
Publisher: Monographs in Epidemiology and
ISBN: 0195050495
Category : Medical
Languages : en
Pages : 310
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Book Description
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.
Author: Harold A. Kahn
Publisher: Monographs in Epidemiology and
ISBN: 0195050495
Category : Medical
Languages : en
Pages : 310
Get Book Here
Book Description
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.
Author: Xinguang Chen
Publisher: Springer Nature
ISBN: 3030352609
Category : Medical
Languages : en
Pages : 420
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Book Description
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.
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: Andrew B. Lawson
Publisher: John Wiley & Sons
ISBN: 1118723171
Category : Medical
Languages : en
Pages : 302
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Book Description
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.
Author: Duncan C. Thomas
Publisher: Oxford University Press
ISBN: 0199748055
Category : Medical
Languages : en
Pages : 458
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Book Description
This well-organized and clearly written text has a unique focus on methods of identifying the joint effects of genes and environment on disease patterns. It follows the natural sequence of research, taking readers through the study designs and statistical analysis techniques for determining whether a trait runs in families, testing hypotheses about whether a familial tendency is due to genetic or environmental factors or both, estimating the parameters of a genetic model, localizing and ultimately isolating the responsible genes, and finally characterizing their effects in the population. Examples from the literature on the genetic epidemiology of breast and colorectal cancer, among other diseases, illustrate this process. Although the book is oriented primarily towards graduate students in epidemiology, biostatistics and human genetics, it will also serve as a comprehensive reference work for researchers. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics will help make the book accessible to those coming from one of these fields without a background in the others. It strikes a good balance between epidemiologic study designs and statistical methods of data analysis.
Author: John M. Lachin
Publisher: John Wiley & Sons
ISBN: 1118625846
Category : Mathematics
Languages : en
Pages : 676
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Book Description
Praise for the First Edition ". . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists." —International Statistical Institute A new edition of the definitive guide to classical and modern methods of biostatistics Biostatistics consists of various quantitative techniques that are essential to the description and evaluation of relationships among biologic and medical phenomena. Biostatistical Methods: The Assessment of Relative Risks, Second Edition develops basic concepts and derives an expanded array of biostatistical methods through the application of both classical statistical tools and more modern likelihood-based theories. With its fluid and balanced presentation, the book guides readers through the important statistical methods for the assessment of absolute and relative risks in epidemiologic studies and clinical trials with categorical, count, and event-time data. Presenting a broad scope of coverage and the latest research on the topic, the author begins with categorical data analysis methods for cross-sectional, prospective, and retrospective studies of binary, polychotomous, and ordinal data. Subsequent chapters present modern model-based approaches that include unconditional and conditional logistic regression; Poisson and negative binomial models for count data; and the analysis of event-time data including the Cox proportional hazards model and its generalizations. The book now includes an introduction to mixed models with fixed and random effects as well as expanded methods for evaluation of sample size and power. Additional new topics featured in this Second Edition include: Establishing equivalence and non-inferiority Methods for the analysis of polychotomous and ordinal data, including matched data and the Kappa agreement index Multinomial logistic for polychotomous data and proportional odds models for ordinal data Negative binomial models for count data as an alternative to the Poisson model GEE models for the analysis of longitudinal repeated measures and multivariate observations Throughout the book, SAS is utilized to illustrate applications to numerous real-world examples and case studies. A related website features all the data used in examples and problem sets along with the author's SAS routines. Biostatistical Methods, Second Edition is an excellent book for biostatistics courses at the graduate level. It is also an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.
Author: Duncan C. Thomas
Publisher: Oxford University Press, USA
ISBN: 0191552682
Category : Medical
Languages : en
Pages : 450
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Book Description
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.
Author: Ray M. Merrill
Publisher: Jones & Bartlett Publishers
ISBN: 1284034437
Category : Epidemiology
Languages : en
Pages : 944
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Book Description
Covers all the core topics, such as digital logic, data representation, machine-level language, general organization, and much more.
Author: Nicholas P. Jewell
Publisher: CRC Press
ISBN: 0203496868
Category : Medical
Languages : en
Pages : 376
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Book Description
Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of "recipes." Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches. Written by one of the top biostatisticians in the field, Statistics for Epidemiology stands apart in its focus on interpretation and in the depth of understanding it provides. It lays the groundwork that all public health professionals, epidemiologists, and biostatisticians need to successfully design, conduct, and analyze epidemiological studies.
Author: Sylvia Wassertheil-Smoller
Publisher: Springer Science & Business Media
ISBN: 1475738870
Category : Science
Languages : en
Pages : 132
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Book Description
Biostatistics and Epidemiology/A Primer for Health Professionals offers practical guidelines and gives a concise framework for research and interpretation in the field. In addition to major sections covering statistics and epidemiology, the book includes a comprehensive exploration of scientific methodology, probability, and the clinical trial. The principles and methods described in this book are basic and apply to all medical subspecialties, psychology and education. The primer will be especially useful to public health officials and students looking for an understandable treatment of the subject.
