Biostatistical Methods in Epidemiology

Comprehensive coverage of classical and modern methods of biostatistics Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; and the analysis of event time data, including the proportional hazards and multiplicative intensity models. The book contains a technical appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods. Biostatistical Methods: The Assessment of Relative Risks: * Presents modern biostatistical methods that are generalizations of the classical methods discussed * Emphasizes derivations, not just cookbook methods * Provides copious reference citations for further reading * Includes extensive problem sets * Employs case studies to illustrate application of methods * Illustrates all methods using the Statistical Analysis System(r) (SAS) Supplemented with numerous graphs, charts, and tables as well as a Web site for larger data sets and exercises, Biostatistical Methods: The Assessment of Relative Risks is an excellent guide for graduate-level students in biostatistics and an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.

A thorough, practical reference on the social patterns behind health outcomes Methods in Social Epidemiology provides students and professionals with a comprehensive reference for studying the social distribution and social determinants of health. Covering the theory, models, and methods used to measure and analyze these phenomena, this book serves as both an introduction to the field and a practical manual for data collection and analysis. This new second edition has been updated to reflect the field's tremendous growth in recent years, including advancements in statistical modeling and study designs. New chapters delve into genetic methods, structural cofounding, selection bias, network methods, and more, including new discussion on qualitative data collection with disadvantaged populations. Social epidemiology studies the way society's innumerable social interactions, both past and present, yields different exposures and health outcomes between individuals within populations. This book provides a thorough, detailed overview of the field, with expert guidance toward the real-world methods that fuel the latest advances. Identify, measure, and track health patterns in the population Discover how poverty, race, and socioeconomic factors become risk factors for disease Learn qualitative data collection techniques and methods of statistical analysis Examine up-to-date models, theory, and frameworks in the social epidemiology sphere As the field continues to evolve, researchers continue to identify new disease-specific risk factors and learn more about how the social system promotes and maintains well-known exposure disparities. New technology in data science and genomics allows for more rigorous investigation and analysis, while the general thinking in the field has become more targeted and attentive to causal inference and core assumptions behind effect identification. It's an exciting time to be a part of the field, and Methods in Social Epidemiology provides a solid reference for any student, researcher, or faculty in public health.

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.

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.

The new edition of this critically praised text continues to provide the most comprehensive overview of the concepts, methods, and research advances in the field. It has been revised and enhanced to capitalize on the strengths of the first edition while keeping it up-to-date in the field of psychiatry. This comprehensive publication now includes new chapters on child psychiatry, community studies, and perinatal studies.

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SU?REZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. P?REZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MART?NEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.

As rapid advances in biotechnology occur, there is a need for a pedagogical tool to aid current students and laboratory professionals in biotechnological methods; Methods in Biotechnology is an invaluable resource for those students and professionals. Methods in Biotechnology engages the reader by implementing an active learning approach, provided advanced study questions, as well as pre- and post-lab questions for each lab protocol. These self-directed study sections encourage the reader to not just perform experiments but to engage with the material on a higher level, utilizing critical thinking and troubleshooting skills. This text is broken into three sections based on level – Methods in Biotechnology, Advanced Methods in Biotechnology I, and Advanced Methods in Biotechnology II. Each section contains 14-22 lab exercises, with instructor notes in appendices as well as an answer guide as a part of the book companion site. This text will be an excellent resource for both students and laboratory professionals in the biotechnology field.

This successful book, now in its third edition, continues to provide a comprehensive introduction to the role of epidemiology in veterinary medicine. Since the publication of the second edition there has been considerable expansion in the application of veterinary epidemiology: more quantitative methods are available, challenges such as the epidemic of foot-and-mouth disease in Europe in 2001 have required epidemiological investigation, and epidemiological analyses have taken on further importance with the emergence of evidence-based veterinary medicine. In this edition: Completely revised and expanded chapters; Increased attention given to the principles and concepts of epidemiology, surveillance, and diagnostic-test validation and performance; Many examples are drawn from both large and small animal medicine, and from the developing as well as the developed world This paperback edition includes a new section on risk analysis. Veterinary Epidemiology is an invaluable reference source for veterinary general practitioners, government veterinarians, agricultural economists and members of other disciplines interested in animal disease. It will also be essential reading for undergraduate and intermediate-level postgraduate students of epidemiology.

Authoritative new text from the experts in GI population studies This book covers both key methodological issues and the most important information in the field, disease by disease. It focuses on population-based information and studies looking at principles and approaches to diagnosis and treatment of diseases. GI Epidemiology brings together world authorities in multiple disciplines for the very first time, to create one clear and comprehensive source. The bulk of the chapters are divided into two parts, covering methodological issues and the epidemiology of specific GI diseases. Each chapter begins with a list of key points, followed by a review written in a clear and simple style. The methodologic chapters cover evidence-based medicine, meta-analysis, systematic reviews, genetic and molecular epidemiology, clinical trials, questionnaire design, and health economics. The disease-specific chapters note the current gaps in knowledge and suggest areas for further study. GI Epidemiology serves as both a useful refresher and a reliable reference on the methods and techniques used in epidemiological studies for consultants and researchers in gastroenterology. It is also an invaluable tool for fellows/trainees in gastroenterology, candidates for recertification in the combined disciplines of gastroenterology, pediatric gastroenterology and colorectal surgery, and anyone completing MPH training.

A comprehensive introduction to the role of epidemiology in veterinary medicine This fully revised and expanded edition of Veterinary Epidemiology introduces readers to the field of veterinary epidemiology. The new edition also adds new chapters on the design of observational studies, validity in epidemiological studies, systematic reviews, and statistical modelling, to deliver more advanced material. This updated edition begins by offering an historical perspective on the development of veterinary medicine. It then addresses the full scope of epidemiology, with chapters covering causality, disease occurrence, determinants, disease patterns, disease ecology, and much more. Veterinary Epidemiology, Fourth Edition: ● Features updates of all chapters to provide a current resource on the subject of veterinary epidemiology ● Presents new chapters essential to the continued advancement of the field ● Includes examples from companion animal, livestock, and avian medicine, as well as aquatic animal diseases ● Focuses on the principles and concepts of epidemiology, surveillance, and diagnostic-test validation and performance ● Includes access to a companion website providing multiple choice questions Veterinary Epidemiology is an invaluable reference for veterinary general practitioners, government veterinarians, agricultural economists, and members of other disciplines interested in animal disease. It is also essential reading for epidemiology students at both the undergraduate and postgraduate levels.