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This book teaches foundations of epidemiological design and statistical methods, as well as including topics applicable to new areas of research. Since the publication of the first edition, Biostatistics and Epidemiology has attracted loyal readers from various specialty areas in the biomedical community. The Fifth Edition includes coverage of fixed and random effects and mixed effects models; Poisson regression; constructing confidence intervals for U-shaped relationships; analysis of rare variants; Mendelian randomization; and aspects of machine learning and big data analytics. Biostatistics and Epidemiology was written to be accessible for readers without backgrounds in mathematics. It provides clear explanations of underlying principles, as well as practical guidelines of'how to do it'and'how to interpret it.'Key features include a philosophical and logical explanation at the beginning of the book, subsections that can stand alone or serve as reference, cross-referencing, recommended reading, and appendices covering sample calculations for various statistics in the text.

This book introduces all common errors in medical science fields and the ways to control them. Systematic errors could be controlled both during study design and statistical analysis. Some errors have been presented in small segments but not in a comprehensive book. It covers many common errors that usually affect the research proposals, final reports, theses, and scientific presentations in the field of medical sciences as well as the rejection reasons on scientific papers. It will help researchers to control common errors using epidemiological and statistical methods.

This book provides a selection of modern and sophisticated methodologies for the analysis of large and complex univariate and multivariate categorical data. It gives an overview of a substantive and broad collection of topics in the analysis of categorical data, including association, marginal and graphical models, time series and fixed effects models, as well as modern methods of estimation such as regularization, Bayesian estimation and bias reduction methods, along with new simple measures for model interpretability. Methodological innovations and developments are illustrated and explained through real-world applications, together with useful R packages, allowing readers to replicate most of the analyses using the provided code. The applications span a variety of disciplines, including education, psychology, health, economics, and social sciences.

Become a disease detective with this easy-to-understand resource Epidemiology For Dummies is packed with key concepts, practical applications, and real-life examples in the study of disease transmission and control. It's a must-have for students in all public-health-related fields, and for curious learners, too. This Dummies guide will help you conquer even the trickiest epidemiological concepts. In this introduction to the fascinating, complex science, you'll learn—in terms anyone can understand—all the basic principles of epidemiology, plus how those concepts translate to public health outcomes and policy decisions. Learn the basic principles and concepts of epidemiology Discover real-world examples and public health threats Understand the complex social factors that influence health Embark on a public health career or just pass your epidemiology courseAnyone who wants or needs to understand the fundamentals of epidemiology and the science behind public health will love Epidemiology For Dummies.

This straightforward primer in basic statistics and epidemiology emphasises their practical use in healthcare and public health, providing understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research. Assuming no prior knowledge, the clarity of the text and care of presentation ensure those new to, or challenged by, these topics are given a thorough introduction without being overwhelmed by unnecessary detail. Key features: Provides an excellent grounding in the basics of both statistics and epidemiology Full step-by-step guidance on performing statistical calculations Numerous examples and exercises with detailed answers to help readers navigate these complex subjects with ease and confidence Enables students and practitioners to make sense of the many research studies that underpin evidence-based practice Fully revised and updated for this fifth edition, now with additional exercises and question and answers online for self-testing An understanding and appreciation of statistics is central to ensuring that professional practice is based on the best available evidence, in order to best treat and help the wider community. Reading this book will help students, researchers, doctors, nurses, and health managers to understand and apply the tools of statistics and epidemiology to their own practice.

This book allows readers to gain an in-depth understanding of the role of real-world data in pharmacoepidemiology, and highlights the strengths and limitations of the respective databases with regard to pharmacoepidemiological research. Over the past decade, the increasing use of real-world data in pharmacoepidemiological research has been accompanied by a growing recognition of the value of real-world evidence in clinical and regulatory decision-making. Electronic healthcare databases allow analyses of drug and vaccine utilization in routine care after approval, as well as investigations of their comparative effectiveness and safety. They are especially useful for the identification of rare risks and rare drug exposures over long periods of time, and as such sustainably extend the basis for drug safety research. This book provides an introduction to the role of real-world data in pharmacoepidemiological research and the main developments in the last 15years. It also offers a comprehensive overview of the general classification characteristics of databases, together with their strengths and limitations, and a detailed description of 21 individual databases, written by professionals who work with or maintain them.

Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students'anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engagingexplanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/

​This unique textbook presents the field of modern epidemiology as a whole; it does not restrict itself to particular aspects. It stresses the fundamental ideas and their role in any situation of epidemiologic practice. Its structure is largely determined by didactic viewpoints.Epidemiology is the art of defining and investigating the influence of factors on the health of populations. Hence the book starts by sketching the role of epidemiology in public health. It then treats the epidemiology of many particular diseases; mathematical modelling of epidemics and immunity; health information systems; statistical methods and sample surveys; clinical epidemiology including clinical trials; nutritional, environmental, social, and genetic epidemiology; and the habitual tools of epidemiologic studies. The book also reexamines the basic difference between the epidemiology of infectious diseases and that of non-infectious ones.The organization of the topics by didactic aspects makes the book ideal for teaching. All examples and case studies are situated in a single country, namely Vietnam; this provides a particularly vivid picture of the role of epidemiology in shaping the health of a population. It can easily be adapted to other developing or transitioning countries.This volume is well suited for courses on epidemiology and public health at the upper undergraduate and graduate levels, while its specific examples make it appropriate for those who teach these fields in developing or emerging countries. New to this edition, in addition to minor revisions of almost all chapters:• Updated data about infectious and non-infectious diseases• An expanded discussion of genetic epidemiology• A new chapter, based on recent research of the authors, on how to build a coherent system of Public Health by using the insights provided by this volume.

This book describes key methods and instruments for assessing diet-related factors, physical activity, social and environmental factors, physical characteristics and health-related outcomes in children and adolescents. These tools were developed and deployed within the framework of the pan-European IDEFICS and I.Family cohort studies. These population-based field studies were funded within the 6th and 7th European Framework Programme, respectively, and were intended to assess the prevalence and aetiology of lifestyle-related diseases in children, focusing on overweight and obesity, and to develop effective strategies for primary prevention. In the course of a decade we undertook a major research endeavour, collecting standardised data from children, families, neighbourhoods, kindergartens, pre-schools and schools in eight European countries, employing a uniform cross-cultural methodology. This resulted in a rich picture of the daily lives and living contexts of children and their families. Studies encompassing childhood and adolescence face the particular challenge of the transitions from pre-school to primary school and from childhood to adolescence; accordingly, the instruments used need to be adapted to different developmental stages while maintaining their comparability across the age range. In young children, questionnaires have to be completed by proxies, usually their parents, while older children, particularly adolescents, can provide a major part of the requested information themselves. This book presents suitable designs, methods and instruments for data collection in studies of children and adolescents. Each chapter explains the development and background of the instruments applied in the surveys and summarises the current state of knowledge. All chapters were written by key experts in their respective research fields. We are grateful for their valuable contributions and their enthusiastic support in producing this book, which also presents survey experiences in which practice does not always follow theory. Participants'responses can on occasion be unexpected and unpredictable, but meeting these challenges can also enrich epidemiological surveys and yield methodological refinements. We sincerely hope that the book and the online material will be of considerable value to other research teams.

The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve problems in quantitative Genetic Epidemiology Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various examples. This clear and concise book covers human genetic epidemiology, using R in data analysis, including multivariate data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology – leading the readers through an effective epidemiologic model, from simple to advanced levels. Classical mathematical, probabilistic, and statistical theory are thoroughly discussed and presented. This book also presents R as a calculator and using R in data analysis. Additionally, it covers Advanced Human Genetic Data Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison. Numerous Worked Examples are provided for illustrations of concepts and real-life applications. Biostatistics for Human Genetic Epidemiology is an ideal reference for professionals and students in Medicine (particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.

This textbook offers a comprehensive analysis of medical decision making under uncertainty by combining Test Information Theory with Expected Utility Theory. The book shows how the parameters of Bayes'theorem can be combined with a value function of health states to arrive at informed test and treatment decisions. The authors distinguish between risk-neutral, risk-averse and prudent decision makers and demonstrate the effects of risk preferences on physicians'decisions. They analyze individual tests, multiple tests and endogenous tests where the test outcome is chosen by the decision maker. Moreover, the topic is examined in the context of health economics by introducing a trade-off between enjoying health and consuming other goods, so that the extent of treatment and thus the potential improvement in the patient's health becomes endogenous. Finally, non-expected utility models of choice under risk and uncertainty (i.e. ambiguity) are presented. While these models can explain observed test and treatment decisions, they are not suitable for normative analyses aimed at providing guidance on medical decision making.

This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods—such as likelihood and estimating function theory—or modeling schemes in varying settings—such as survival analysis and longitudinal data analysis—can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.

Since the publication of the first edition, Biostatistics and Epidemiology has attracted loyal readers from across specialty areas in the biomedical community. Not only does this textbook teach foundations of epidemiological design and statistical methods, but it also includes topics applicable to new areas of research. Areas covered in the fourth edition include a new chapter on risk prediction, risk reclassification and evaluation of biomarkers, new material on propensity analyses, and a vastly expanded chapter on genetic epidemiology, which is particularly relevant to those who wish to understand the epidemiological and statistical aspects of scientific articles in this rapidly advancing field. Biostatistics and Epidemiology was written to be accessible for readers without backgrounds in mathematics. It provides clear explanations of underlying principles, as well as practical guidelines of'how to do it'and'how to interpret it.'Key features include a philosophical and logical explanation at the beginning of the book, subsections that can stand alone or serve as reference, cross-referencing, recommended reading, and appendices covering sample calculations for various statistics in the text.

This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.

Die Proceedings der 35. Jahrestagung der Gesellschaft für Medizinische Dokumentation, Informatik und Statistik geben einen Überblick über die derzeit wichtigen Forschungsschwerpunkte der Epidemiologie. Dabei konnten zum ersten Mal auch Beiträge aus der ehemaligen DDR in größerer Zahl eingebracht werden. Schwerpunkte des Proceedingsbandes bilden die Epidemiologie kardiovaskulärer Erkrankungen, die Umweltepidemiologie, die Epidemiologie von Berufskrankheiten und das epidemiologische Monitoring von Krebserkrankungen und Infektionskrankheiten. Die Qualität verfügbarer Datenquellen wird kritisch diskutiert und die Bedeutung der Epidemiologie für eine Verbesserung der Gesundheitsberichterstattung in den alten und in den neuen Bundesländern klargelegt. Darüber hinaus werden methodische Probleme und unterstützende Techniken der Medizinischen Informatik angesprochen.

This Companion Textbook supplements the ActivEpi CD-ROM, sold separately. The ActivEpi CD-ROM provides a multimedia presentation of concepts, commonly taught in an introductory epidemiology course. ActivEpi mixes a full array of media to motivate, explain, visualize and apply epidemiological concepts. Virtually all of the material on the ActivEpi CD-ROM is included in the Companion Textbook. Because individuals differ in their learning skills, the ActivEpi CD-ROM and the ActivEpi Companion Textbook offer readers different but related options on how to learn epidemiology. The Textbook can be used as a hardcopy reference of the textual materials contained on the CD-ROM, as a resource for the practice exercises, as a general reference, or even a self-contained textbook. ActivEpi includes 15 lessons and over 50 hours of content via more than 250 launchable activities and homework exercises. It can be used in a variety of teaching formats: distance learning, self-paced learning, on-campus courses, and short courses. For the latest additions to ActivEpi, visit David Kleinbaum's website.

Translating the evidence from the bedside to populations This sixth edition of the best-selling Epidemiology, Evidence-based Medicine and Public Health Lecture Notes equips students and health professionals with the basic tools required to learn, practice and teach epidemiology and health prevention in a contemporary setting. The first section, ‘Epidemiology', introduces the fundamental principles and scientific basis behind work to improve the health of populations, including a new chapter on genetic epidemiology. Applying the current and best scientific evidence to treatment at both individual and population level is intrinsically linked to epidemiology and public health, and has been introduced in a brand new second section: ‘Evidence-based Medicine'(EBM), with advice on how to incorporate EBM principles into your own practice. The third section,'Public Health', introduces students to public health practice, including strategies and tools used to prevent disease, prolong life, reduce inequalities, and includes global health. Thoroughly updated throughout, including new studies and cases from around the globe, key learning features include: Learning objectives and key points in every chapter Extended coverage of critical appraisal and data interpretation A brand new self-assessment section of SAQs and'True/False'questions for each topic A glossary to quickly identify the meaning of key terms, all of which are highlighted for study and exam preparation Further reading suggestions on each topic Whether approaching these topics for the first time, starting a special study module or placement, or looking for a quick-reference summary, this book offers medical students, junior doctors, and public health students an invaluable collection of theoretical and practical information.

The European Federation for Medical Informatics has established itself as a regional body coordinating activity in medical informatics. The Congress in Toulouse, MIE-81, from 9 - 13 March 1981, is the third congress in the ser ies following MIE-78 in Cambr idge, and MIB-79 in Berlin with a gap during 1980 for the world congress MEDINFO-80 in Tokyo. The rationale behind all these congresses is the scientific need to share results and ideas and the educational need to train a wide variety of professional staff in the potential of health care and medical informatics. All the caring professions are involved, doctors, scientists, nurses, para-medical staff, administrators, health care planners, community physicians, epidemiologists, statisticians, operations analysts together with specialists from the computing profession dealing with system analysis, hardware, software, languages, data-bases and the marketing of systems. Medical Informatics is a very wide subject with ramifications throughout the health care and preventive services; it offers a key to the monitoring and improvement of patient care and to the provision of a healthier environment. The collection and evaluation of relevant data improves our understanding of the ways in which health care is provided while the availability of cheaper computer hardware and more versatile software enables us to design and implement more revealing and intelligent medical systems. Even though typical systems take a substantial amount of time to design, implement and evaluate, there is the continuing need for informaticians to assess the current state of developmen.

In February 1985 a small international meeting of scientists took place at the recreation resort of the Polish Academy of Sci­ ences in Mogilany, near Cracow, Poland. The initiative for holding the workshop came from a working meeting on mathematical immunology and related topics at the International Institute for Applied Sys­ tems Analysis in Laxenburg, Austria, in November 1983. In addition to representatives of IIASA, delegates of the IIASA National Member Organizations (NMO) of Czechoslovakia, Italy, and the soviet Union took part in that working meeting. The participants came to the conclusion that IIASA could play an important role in facilitating the development of research in this field. The first step that they recommended to I IASA was to organize a workshop on mathematical immunology. The purpose of the workshop was to review the progress that has been made in applying mathematics to problems in immunology and to explore ways in which further progress might be achieved, especially by more efficient interactions between scientists working in mathematical and experimental immunology. Some National Member Organizations contributed to the success of the workshop by nominat­ ing further participants working in this or related fields. For instance, thanks to a suggestion of the British NMO, the meeting also included analyses of the interactions between the immune state of a population and epidemiological phenomena. There were 33 participants at Mogilany from 11 countries, namely Canada, Czechoslovakia, Federal Republic of Germany, Hungary, Japan, Netherlands, Poland, Sweden, united Kingdom, USA, and USSR.

Guillaume Wunsch, Michel Mouchart, Josianne Duchene This book is an outcome of the activities of the Working Group on Health, Morbidity, and Mortality Differentials of the European Association for Population Studies, which was chaired for some years by one of the present editors (G. Wunsch). In collaboration with the Institute of Statistics and the Institute of Demography of the University of Louvain, this Working Group held a workshop in Louvain-Ia-Neuve a few years ago on the use of life tables in Europe, taking into account problems of data collection, methods, and models. Some of the participants in the workshop were then invited by the present editors to improve, develop, or in some cases thoroughly modify their papers in order to transform them into chapters of a book on life tables. Though life tables are one of the oldest tools in demography, and every textbook on demographic methods deals with the topic of life table construction, few books have dealt with the subject in depth. It is the hope of the editors that the present volume will fulfill to some extent this need. Though primarily written by and for demographers, this book will also be of use to actuaries working in life insurance, and to epidemiologists dealing with morbidity and cause of death. Furthermore, a topic such as competing risks theory should also be of interest to statisticians.

This textbook presents epidemiology in a practical manner, contextualized with discussions of theory and ethics, so that students and professionals from all academic backgrounds may develop a deep appreciation for how to conduct and interpret epidemiological research. Readers will develop skills to: -Search for and appraise literature critically, -Develop important research questions, -Design and implement studies to address those questions, -Perform and interpret fundamental statistical estimations and tests, -Consider the ethical implications of all stages of research, -Report findings in publications, and -Advocate for change in the public health setting. Epidemiology is and will remain a discipline in motion, and this textbook aims at reflecting this dynamism and keeping pace with its momentum. This textbook is not only a classroom tool with high utility but also an essential reference and guide for those engaging in research involving human subjects.

Here is a book for clinicians, clinical investigators, trainees, and graduates who wish to develop their proficiency in the planning, execution, and interpretation of clinical and epidemiological research. Emphasis is placed on the design and analysis of research studies involving human subjects where the primary interest concerns principles of analytic (cause-and- effect) inference. The topic is presented from the standpoint of the clinician and assumes no previous knowledge of epidemiology, research design or statistics. Extensive use is made of illustrative examples from a variety of clinical specialties and subspecialties. The book is divided into three parts. Part I deals with epidemiological research design and analytic inference, including such issues as measurement, rates, analytic bias, and the main forms of observational and experimental epidemiological studies. Part II presents the principles and applications of biostatistics, with emphasis on statistical inference. Part III comprises four chapters covering such topics as diagnostic tests, decision analysis, survival (life-table) analysis, and causality.

The papers in this volume discuss important methodological advances in several important areas, including multivariate failure time data and interval censored data. The book will be an indispensable reference for researchers and practitioners in biostatistics, medical research, and the health sciences.

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.

This book is meant for adoption in first courses on epidemiology in Medical Schools and Faculties of Public Health in developing and transition countries and in workshops in these countries, taught for example by members of international organizations. It is also suitable for parallel or second reading within curricula in developed countries and for teaching epidemiology in a Master's programme on “International Health”. The book will enable any lecturer to compose his or her introductory courses on epidemiology by selecting the material deemed appropriate. It will provide a solid foundation for more advanced teaching.The intended readership consists in the first place of general medical students; students following the programme “Preventive Physician” that runs parallel to general medical studies in some countries; students starting to specialize in Public Health; and lecturers in epidemiology. The book can also serve well as an introduction into epidemiology for anybody else interested in this field, for example staff of health institutions.Examples and practical work are taken from the present situation of health in Vietnam, which can easily be adapted to any other developing or transition country.

This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on'Design and Analysis of Clinical Trials'and'Statistics and Epidemiology: Environment and Health.'This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on'Statistics in the Health Sciences.'I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti­ tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop­ kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.

Written by Peter J. Fos—an expert in epidemiology with more than twenty years teaching experience—Epidemiology Foundations offers an ideal introduction to the theory and practice of public health epidemiology. This important text discusses both the historical perspective and future trends of epidemiology, reviews health and disease, and explains how they are measured. The book's overview of epidemiological studies shows how they are used in practice. Epidemiology Foundations takes a social and community perspective and includes information about global diseases and epidemics. Emphasis on concepts such as population health, social determinants, and global health make this book especially interesting and accessible to those new to the subject. Each chapter is supplemented with problem-solving exercises and research assignments to aid readers in understanding its epidemiology principles. Reflecting and expanding on recommendations of the Association of American Colleges and Universities, Epidemiology Foundations is the ideal text for any course introducing epidemiology in public health.

Hardly a day goes by without news headlines concerning infectious disease threats. Currently the spectre of a pandemic of influenza A|H1N1 is raising its head, and heated debates are taking place about the pro's and con's of vaccinating young girls against human papilloma virus. For an evidence-based and responsible communication of infectious disease topics to avoid misunderstandings and overreaction of the public, we need solid scientific knowledge and an understanding of all aspects of infectious diseases and their control. The aim of our book is to present the reader with the general picture and the main ideas of the subject. The book introduces the reader to methodological aspects of epidemiology that are specific for infectious diseases and provides insight into the epidemiology of some classes of infectious diseases characterized by their main modes of transmission. This choice of topics bridges the gap between scientific research on the clinical, biological, mathematical, social and economic aspects of infectious diseases and their applications in public health. The book will help the reader to understand the impact of infectious diseases on modern society and the instruments that policy makers have at their disposal to deal with these challenges. It is written for students of the health sciences, both of curative medicine and public health, and for experts that are active in these and related domains, and it may be of interest for the educated layman since the technical level is kept relatively low.

The leading text in the field, this comprehensive book reviews geographic approaches to studying disease and public health issues across the globe. It presents cutting-edge techniques of spatial and social analysis and explores their relevance for understanding cultural and political ecology, disease systems, and health promotion. Essential topics include how new diseases emerge and epidemics develop in particular places; the intersecting influences on health of biological processes, culture, environment, and behavior; and the changing landscape of health care planning and service delivery. The text is richly illustrated with tables, figures, and maps, including 16 color plates.

A collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges in industrialized countries. They are characterized by the systems properties of gene networks and their interrelations, instead of individual genes, whose malfunctioning manifests in pathological phenotypes, thus making the analysis of the resulting large data sets particularly challenging. This is why novel approaches are needed to tackle this problem efficiently on a systems level. Written by computational biologists and biostatisticians, this book is an invaluable resource for a large number of researchers working on basic but also applied aspects of biomedical data analysis emphasizing the pathway level.

This textbook was born from a disparate collection of written materials that were created to teach Epidemiology and Biostatistics to second year medical students at the University of Washington. These materials included handouts, practice problems, guides to reading research articles, quizzes, notes from student help sessions, and student emails. The primary goal of these written materials, and now this book, is to recreate the perspective of learning Epidemiology and Biostatistics for the first time. With critical editing assistance from Epidemiology faculty, graduate students in Epidemiology and Biostatistics, and the students themselves, I have tried to preserve the innate logic and connectedness of clinical research methods and to demonstrate their application. The textbook is designed to provide students with the tools necessary to form their own informed conclusions from the clinical research literature. More than ever, a clear understanding of the fundamental aspects of Epidemiology and Biostatistics is needed to successfully navigate the increasingly complex methods utilized by modern clinical research studies. This book could not have been created without the dedicated help of the e- tors, the teaching assistants, and the students, who asked the important questions. I would especially like to thank my family who patiently allowed me so much time to write.

Widespread immunization has many different kinds of effects in individuals and populations, including in the unvaccinated individuals. The challenge is in understanding and estimating all of these effects. This book presents a unified conceptual framework of the different effects of vaccination at the individual and at the population level. The book covers many different vaccine effects, including vaccine efficacy for susceptibility, for disease, for post-infection outcomes, and for infectiousness. The book includes methods for evaluating indirect, total and overall effects of vaccination programs in populations. Topics include household studies, evaluating correlates of immune protection, and applications of casual inference. Material on concepts of infectious disease epidemiology, transmission models, casual inference, and vaccines provides background for the reader. This is the first book to present vaccine evaluation in this comprehensive conceptual framework. This book is intended for colleagues and students in statistics, biostatistics, epidemiology, and infectious diseases. Most essential concepts are described in simple language accessible to epidemiologists, followed by technical material accessible to statisticians. M. Elizabeth Halloran and Ira Longini are professors of biostatistics at the University of Washington and the Fred Hutchinson Cancer Research Center in Seattle. Claudio Struchiner is professor of epidemiology and biostatistics at the Brazilian School of Public Health of the Oswaldo Cruz Foundation in Rio de Janeiro. The authors are prominent researchers in the area. Halloran and Struchiner developed the study designs for dependent happenings to delineate indirect, total, and overall effects. Halloran has made contributions at the interface of epidemiological methods, causal inference, and transmission dynamics. Longini works in the area of stochastic processes applied to epidemiological infectious disease problems, specializingin the mathematical and statistical theory of epidemics. Struchiner has contributed to understanding the role of transmission in interpreting vaccine effects.

The abstract concept of “information” can be quantified and this has led to many important advances in the analysis of data in the empirical sciences. This text focuses on a science philosophy based on “multiple working hypotheses” and statistical models to represent them. The fundamental science question relates to the empirical evidence for hypotheses in this set—a formal strength of evidence. Kullback-Leibler information is the information lost when a model is used to approximate full reality. Hirotugu Akaike found a link between K-L information (a cornerstone of information theory) and the maximized log-likelihood (a cornerstone of mathematical statistics). This combination has become the basis for a new paradigm in model based inference. The text advocates formal inference from all the hypotheses/models in the a priori set—multimodel inference. This compelling approach allows a simple ranking of the science hypothesis and their models. Simple methods are introduced for computing the likelihood of model i, given the data; the probability of model i, given the data; and evidence ratios. These quantities represent a formal strength of evidence and are easy to compute and understand, given the estimated model parameters and associated quantities (e.g., residual sum of squares, maximized log-likelihood, and covariance matrices). Additional forms of multimodel inference include model averaging, unconditional variances, and ways to rank the relative importance of predictor variables. This textbook is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals in various universities, agencies or institutes. Readers are expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameterestimation.

Statistical methods have become an increasingly important and integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an'International Conference on Statistics in Health Sciences,'covers a wide range of topics pertaining to new statistical methods in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas: prognostic studies and general epidemiology, pharmacovigilance, quality of life, survival analysis, clustering, safety and efficacy assessment, clinical design, models for the environment, genomic analysis, and animal health. This comprehensive volume will serve the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics.

This 3-volume reference covers the entire field of epidemiology, from statistical methods and study design, to specialized areas such as molecular epidemiology, and applications in clinical medicine and health services research. This updated edition of the Handbook of Epidemiology adds 22 new chapters on: History of Epidemiological Methods and Concepts, Cluster Randomized Trials, Internet-Based Epidemiology, Misclassification, Sensitivity Analysis and Bias Analysis, Emergency and Disaster Health Surveillance, Statistical Inference, Data Management in Epidemiology, Visual Display of Quantitative Information, Bayesian Methods in Epidemiology, Generalized Estimating Equations, Directed Acyclic Graphs, Life Course Epidemiology, Molecular Epidemiology, Physical Activity, Radiation Epidemiology, Epidemiology of Obesity, Epidemiology of Respiratory Allergies and Asthma, Epidemiology of Dental Diseases, Epidemiology of Digestive Diseases, Psychiatric Disorders, Epidemiology of Diabetes.All other chapters are extensively revised from the 1st edition. This is a reference for epidemiological researchers and graduate students in public health.

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.

Arranged to facilitate use and highlight key concepts, this clear and concise text also includes many practical exercises, case studies, and real-world applications. Utilizing the modern biostatistical approach to studying disease, Epidemiology Kept Simple, Second Edition will provide readers with the tools to interpret epidemiological data, understand disease concepts, and prepare for board exams. The author fully explains all new terminology and minimizes the use of technical language, while emphasizing real-life practice in modern public health and biomedical research settings.

This is the second edition of this text on logistic regression methods, ori- nally published in 1994. As in the first edition, each chapter contains a presentation of its topic in “lecture-book” format together with objectives, an outline, key formulae, practice exercises, and a test. The “lecture-book” has a sequence of illust- tions and formulae in the left column of each page and a script (i.e., text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This second edition has expanded the first edition by adding five new ch- ters and a new appendix. The five new chapters are Chapter 9. Polytomous Logistic Regression Chapter 10. Ordinal Logistic Regression Chapter 11. Logistic Regression for Correlated Data: GEE Chapter 12. GEE Examples Chapter 13. Other Approaches for Analysis of Correlated Data Chapters 9 and 10 extend logistic regression to response variables that have more than two categories. Chapters 11–13 extend logistic regression to gen- alized estimating equations (GEE) and other methods for analyzing cor- lated response data. The appendix is titled “Computer Programs for Logistic Regression” and p- vides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The so- ware packages considered are SAS Version 8.0, SPSS Version 10.0, and STATA Version 7.0.

This text on smvival analysis methods contains the following chapters: 1 Introduction to Smvival Analysis 2 Kaplan-Meier Survival Curves and the Log-Rank Test 3 The Cox Proportional Hazards Model and Its Characteristics 4 Evaluating the Proportional Hazards Assumption 5 The Stratified Cox Procedure 6 Extension of the Cox Proportional Hazards Model for Time­ Dependent Variables Each chapter contains a presentation of its topic in'1ecture-book'format together with objectives, an outline, key formulae, practice exercises, and a test. The'lecture-book'has a sequence of illustrations and formulae in the left column of each page and a script in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that high­ light the main points, formulae, or examples being presented. The reader may also purchase directly from the author audio cassette tapes of each chapter. The use of the audiotape with the illustrations and formu­ lae, ignoring the script, is intended to be similar to a lecture. Tapes may be obtained by writing or calling the author at the following address: Depart­ ment of Epidemiology, Rollins School of Public Health, Emory University, 1518 CliftoIi Rd. N. E., Atlanta, GA 30322; phone (404) 727-9667. This text is intended for self-study.

Focusing on areas of public health practice in which the systematic application of epidemiologic methods can have a large and positive impact, this text applies traditional epidemiologic methods for determining disease etiology to the'real-life'applications of public health and health services research. Brownson and Petitti--true to their belief that epidemiology is the diagnostic discipline of public health--provide a much-needed book that bridges the gap between theoretical epidemiology and public health practice. Their uniquely comprehensive coverage includes a number of topics not traditionally addressed by other epidemiology texts. Twelve chapters offer a thorough, in-depth analysis of the important issues, methods, problems, and limitations within applied epidemiology. Following an introduction, three overview chapters detail study design and interpretation, outbreak and cluster investigations, and public health surveillance. The remaining chapters highlight key issues and provide practical recommendations on eight contemporary topics, such as community intervention trials, outcomes research, risk assessment, screening, and cost-benefit analysis. The editors--both very well-known researchers in the field--have compiled reviews with direct relevance to or a strong basis in epidemiology. All chapters have been authored by recognized authorities in the field of epidemiology and public health. Case studies of actual programs at the end of each chapter illustrate major points and provide a foundation for more detailed discussions. Applied Epidemiology is intended for practitioners in epidemiology, and students in epidemiology and related disciplines that rely heavily on epidemiologic methods and reasoning. It will be a practical and informative tool in academic institutions, federal agencies with significant educational missions, state and local public health agencies, and health care organizations.