Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. Key Features * Provides a synthesis of the epidemiological and philosophical concepts in this growing research area * Gives an accessible overview of current methods in biomedical causal metaphysics what is a cause of illness? and epistemology how do we identify it? * Proposes a novel approach that integrates modern epidemiological methodology and recent theories from philosophy of science Written for postgraduate students and researchers in the health and biomedical sciences, including those undertaking courses in the philosophy of medicine/science, public and global health, introduction to epidemiology, research methods, and advanced reasoning, the content will also be of interest to practicing public health workers, biomedical scientists, and physicians. ABOUT THE AUTHOR Olaf Dammann is Professor and Vice Chair of Public Health and Community Medicine at Tufts University School of Medicine, Boston, Massachusetts, USA; as well as a Professor in the Department of Gynecology and Obstetrics at Hannover Medical School, Hannover, Germany. Cover image: Mask used by "Eskimo" shaman in causation of illness. Credit: Wellcome Collection. CC BY https://creativecommons.org/licenses/by/4.0

Epidemiology is often referred to as the science of public health. However, unlike other major sciences, its theoretical foundations are rarely articulated. While the idea of epidemiologic theory may seem dry and arcane, it is at its core about explaining the people's health. It is about life and death. It is about biology and society. It is about ecology and the economy. It is about how myriad aspects of people's lives - involving work, dignity, desire, love, play, conflict, discrimination, and injustice - become literally incorporated into our bodies and manifest in our health status, individually and collectively. And it is about essential knowledge critical for improving the people's health and minimizing inequitable burdens of disease, disability, and death. Woven from a vast array of schools of thought, including those in the natural, social, and biomedical sciences, epidemiologic theory is a rich tapestry whose time for analysis is long overdue. By tracing its history and contours from ancient societies on through the development of - and debates within - contemporary epidemiology worldwide, Dr. Krieger shows how epidemiologic theory has long shaped epidemiologic practice, knowledge, and the politics of public health. Outlining an ecosocial theory of disease distribution that situates both population health and epidemiologic theory in societal and ecologic context, she offers a more holistic picture of how we embody the human experience. This concise, conceptually rich, and accessible book is a rallying cry for a return to the study and discussion of epidemiologic theory: what it is, why it matters, how it has changed over time, and its implications for improving population health and promoting health equity. It should be required reading for all epidemiologists, or anyone involved in the study of human health and well-being.

Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic.

The number of innovative applications of randomization tests in various fields and recent developments in experimental design, significance testing, computing facilities, and randomization test algorithms have necessitated a new edition of Randomization Tests. Updated, reorganized, and revised, the text emphasizes the irrelevance and implausibility of the random sampling assumption for the typical experiment in three completely rewritten chapters. It also discusses factorial designs and interactions and combines repeated-measures and randomized block designs in one chapter. The authors focus more attention on the practicality of N-of-1 randomization tests and the availability of user-friendly software to perform them. In addition, they provide an overview of free and commercial computer programs for all of the tests presented in the book. Building on the previous editions that have served as standard textbooks for more than twenty-five years, Randomization Tests, Fourth Edition includes downloadable resources of up-to-date randomization test programs that facilitate application of the tests to experimental data. This CD-ROM enables students to work out problems that have been added to the chapters and helps professors teach the basics of randomization tests and devise tasks for assignments and examinations.

Develop a Deep Understanding of the Statistical Issues of APC Analysis Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approach. See How Common Methods Are Related to Each Other After a general and wide-ranging introductory chapter, the book explains the identification problem from algebraic and geometric perspectives and discusses constrained regression. It then covers important strategies that provide information that does not directly depend on the constraints used to identify the APC model. The final chapter presents a specific empirical example showing that a combination of the approaches can make a compelling case for particular APC effects. Get Answers to Questions about the Relationships of Ages, Periods, and Cohorts to Important Substantive Variables This book incorporates several APC approaches into one resource, emphasizing both their geometry and algebra. This integrated presentation helps researchers effectively judge the strengths and weaknesses of the methods, which should lead to better future research and better interpretation of existing research.

Written by a biostatistics expert with over 20 years of experience in the field, Bayesian Methods in Epidemiology presents statistical methods used in epidemiology from a Bayesian viewpoint. It employs the software package WinBUGS to carry out the analyses and offers the code in the text and for download online. The book examines study designs that investigate the association between exposure to risk factors and the occurrence of disease. It covers introductory adjustment techniques to compare mortality between states and regression methods to study the association between various risk factors and disease, including logistic regression, simple and multiple linear regression, categorical/ordinal regression, and nonlinear models. The text also introduces a Bayesian approach for the estimation of survival by life tables and illustrates other approaches to estimate survival, including a parametric model based on the Weibull distribution and the Cox proportional hazards (nonparametric) model. Using Bayesian methods to estimate the lead time of the modality, the author explains how to screen for a disease among individuals that do not exhibit any symptoms of the disease. With many examples and end-of-chapter exercises, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how these Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors.

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. The book is designed not only for biopharmaceutical professionals, such as statisticians, safety specialists, pharmacovigilance experts, and pharmacoepidemiologists, who can use the book as self-learning materials or in short courses or training programs, but also for graduate students in statistics and biomedical data science for a one-semester course. Each chapter provides supplements and problems as more readings and exercises.

When Peter Piot was in medical school, a professor warned, "There's no future in infectious diseases. They've all been solved." Fortunately, Piot ignored him, and the result has been an exceptional, adventure-filled career. In the 1970s, as a young man, Piot was sent to Central Africa as part of a team tasked with identifying a grisly new virus. Crossing into the quarantine zone on the most dangerous missions, he studied local customs to determine how this disease-the Ebola virus-was spreading. Later, Piot found himself in the field again when another mysterious epidemic broke out: AIDS. He traveled throughout Africa, leading the first international AIDS initiatives there. Then, as founder and director of UNAIDS, he negotiated policies with leaders from Fidel Castro to Thabo Mbeki and helped turn the tide of the epidemic. Candid and engrossing, No Time to Lose captures the urgency and excitement of being on the front lines in the fight against today's deadliest diseases.

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 Ornulf 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.

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

Take Your NI Trial to the Next Level Reflecting the vast research on noninferiority (NI) designs from the past 15 years, Noninferiority Testing in Clinical Trials: Issues and Challenges explains how to choose the NI margin as a small fraction of the therapeutic effect of the active control in a clinical trial. Requiring no prior knowledge of NI testing, the book is easily accessible to both statisticians and nonstatisticians involved in drug development. With over 20 years of experience in this area, the author introduces the basic elements of the NI trials one at a time in a logical order. He discusses issues with estimating the effect size based on historical placebo control trials of the active control. The book covers fundamental concepts related to NI trials, such as assay sensitivity, constancy assumption, discounting, and preservation. It also describes patient populations, three-arm trials, and the equivalence of three or more groups.

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.

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. Key Features * Provides a synthesis of the epidemiological and philosophical concepts in this growing research area * Gives an accessible overview of current methods in biomedical causal metaphysics what is a cause of illness? and epistemology how do we identify it? * Proposes a novel approach that integrates modern epidemiological methodology and recent theories from philosophy of science Written for postgraduate students and researchers in the health and biomedical sciences, including those undertaking courses in the philosophy of medicine/science, public and global health, introduction to epidemiology, research methods, and advanced reasoning, the content will also be of interest to practicing public health workers, biomedical scientists, and physicians. ABOUT THE AUTHOR Olaf Dammann is Professor and Vice Chair of Public Health and Community Medicine at Tufts University School of Medicine, Boston, Massachusetts, USA; as well as a Professor in the Department of Gynecology and Obstetrics at Hannover Medical School, Hannover, Germany. Cover image: Mask used by "Eskimo" shaman in causation of illness. Credit: Wellcome Collection. CC BY https://creativecommons.org/licenses/by/4.0

Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.

This updated second edition of Molecular Typing in Bacterial Infections, presented in two volumes, covers both common and neglected bacterial pathogenic agents, highlighting the most effective methods for their identification and classification in the light of their specific epidemiology. New chapters have been included to add new species, as well as another view of how bacterial typing can be used. These books are valuable resources for the molecular typing of infectious disease agents encountered in both research and hospital clinical laboratory settings, as well as in culture collections and in the industry. Each of the 21 chapters provides an overview of specific molecular approaches to efficiently detect and type different bacterial pathogens. The chapters are grouped in five parts, covering respiratory and urogenital pathogens (Volume I), and gastrointestinal and healthcare-associated pathogens, as well as a new group of vector-borne and Biosafety level 3 pathogens including a description of typing methods used in the traditional microbiology laboratory in comparison to molecular methods of epidemiology (Volume II). Comprehensive and updated, Molecular Typing in Bacterial Infections provides state-of-the-art methods for accurate diagnosis and for the correct classification of different types which will prove to be critical in unravelling the transmission routes of human pathogens.

The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1) Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs: A perspective on the role of the intention-to-treat principle Examples and case studies from various areas Example code in SAS and R A connection with causal inference Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.

With COVID-19 sweeping across the globe with near impunity, it is thwarting governments and health organizations efforts to contain it. Not since the 1918 Spanish Flu have citizens of developed countries experienced such a large-scale disease outbreak that is having devastating health and economic impacts. One reason such outbreaks are not more common has been the success of the public health community, including epidemiologists and biostatisticians, in identifying and then mitigating or eliminating the outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often crucially depends on statistical methods to help discern whether an outbreak may be occurring and, if there is sufficient evidence of an outbreak, then to locate and track it. Statisticians also help collect critical information, and they analyze the resulting data to help investigators zero in on a cause for a disease. With the recent outbreaks of diseases such as swine and bird flu, Ebola, and now COVID-19, the role that epidemiologists and biostatisticians play is more important than ever. Features: * Discusses the crucial roles of statistics in early disease detection. * Outlines the concepts and methods of disease surveillance. * Covers surveillance techniques for communicable diseases like Zika and chronic diseases such as cancer. * Gives real world examples of disease investigations including smallpox, syphilis, anthrax, yellow fever, and microcephaly (and its relationship to the Zika virus). Via the process of identifying an outbreak, finding its cause, and developing a plan to prevent its reoccurrence, this book tells the story of how medical and public health professionals use statistics to help mitigate the effects of disease. This book will help readers understand how statisticians and epidemiologists help combat the spread of such diseases in order to improve public health across the world.

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 ollution, this text provides a systematic treatment of the statistical challenges that arise in environmental health studies and the use of 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 studies aimed 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 global warming, 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.

The consequences of childhood obesity are serious and far reaching, with both physical and psychological components that add to its complexity. Childhood Obesity: Contemporary Issues provides an up-to-date account of the increase of obesity in children, its causes, and its prevention. The expert editorial panel has chosen contributors with considerable practical and research experience. They explore why childhood obesity is so difficult to prevent and treat. Focusing less on clinical issues and more on environmental factors, the book brings together social, psychological, biological, and socio-biological approaches to the experience and problem of obesity. Delineating the scope and impact of childhood obesity, the book provides a unique view of the obese child. It examines the link between food intake and physical activity, which are the immediate determinants of energy balance, and discusses how to measure and assess them. The World Health Organization describes obesity as one of today's most blatantly visible - yet most neglected - public health problems. This book highlights obesity in children and discusses the need to develop multifactorial and multi-agency strategic plans to contain this epidemic.

This volume is comprised of papers presented at the Third International Conference on Pharmacoepidemiology, held September 9-11, 1987, in Minneapolis, Minnesota. The book is divided into four sections, which reflect the four themes of the conference: Social Impact of Pharmacoepidemiology; Drug Epidemiology and the Law; Drug Surveillance; and Drugs, Populations, and Outcomes: Specific Studies. The collection of papers discusses the social and legal impact of epidemiology, the system of checks and balances that is necessary for the field, the importance of core support for researchers, and the goal of an enlightened and informed public, including the media, consumer advocates, and the courts. Contributing authors offer perspectives from academia, practice, government, industry and the law. Numerous tables and figures are included to illustrate many of the papers within the text. This book offers substantial reading for epidemiologists and individuals interested in the field of pharmacoepidemiology.

Introductory Medical Statistics, now in its third edition, is an introductory textbook on basic statistical techniques. It is written for physicians, surgeons, radiation oncologists, medical physicists, radiographers, hospital administrators, medical statisticians in training, biochemists, and other professionals allied to medicine. It is suitable as a teaching text for clinicians working towards their professional examinations. It is also suitable for Maters degree courses in medical physics. The third edition has been extensively revised and expanded to include: Clinical trial design and analysis] Multivariate analysis Cox proportional hazards model McNemar, Wicoxon, Mann-Whitney, Kruskal-Wallis, Mantel-Haenszel, and Kappa tests Kaplan-Meier survival rates Sensitivity and Specificity Specification of treatment success, cure, and quality of life Risk specification Case-control and cohort epidemiological studies Glossary of terms The major change has been the advent of personal computing, so people rely on the power of their machine, and its software to number crunch. What is missing is that the software may not use the appropriate statistical error standard - Dick Mould

This completely revised and updated edition of an outstanding text addresses the fundamental knowledge of epidemiological methods and statistics that can be applied to evolving systems, programs, technologies, and policies. This edition presents new chapters on causal thinking, ethics, and web resources, analyzes data on multinational increases in poverty and longevity, details the control of transmissible diseases, and explains quality management, and the evaluation of healthcare system performance.

Viruses do not behave as other microbes; their life cycles require infecting healthy cells, commandeering their cellular apparatus, replicating and then killing the host cell. Methods for virus detection and identification have been developed only in the past few decades. These recently developed methods include molecular, physical, and proteomic techniques. All these approaches (Electron Microscopy, Molecular, Direct Counting, and Mass Spectrometry Proteomics) to detection and identification are reviewed in this succinct volume. It is written in approachable language with enough detail for trained professionals to follow and want to recommend to others. Key Features Covers common detection methods Reviews the history of detection from antiquity to the present Documents the strengths and weaknesses of various detection methods Describes how to detect newly discovered viruses Recommends specific applications for clinical, hospital, environmental, and public health uses

Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful "Essentials of Biostatistics" has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures.

This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes' theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text.

Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.

TEXTBOOK OF EPIDEMIOLOGY The gold standard in epidemiological texts In the second edition of Textbook of Epidemiology, a distinguished team of researchers deliver an extensively updated and comprehensive exploration of epidemiological methods, illuminating the tools for studying the distribution and risk factors of health states and events in populations. An introduction to epidemiological methods with recent and broadly applicable examples End-of-chapter self-assessment questions for readers to check their understanding of key concepts, with answer keys and further enrichment materials available on a companion website A brand-new chapter covering methods for systematic reviews and meta-analysis Accessible material appropriate for clinical practitioners and researchers from around the world Perfect for professionals working in clinical medicine and public health, Textbook of Epidemiology will also earn a place in the libraries of allied health professionals seeking a one-stop resource or to re-immerse themselves in specific methodological topics and practices.