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| statistics for epidemiology: Statistics for Epidemiology Nicholas P. Jewell, 2003-08-26 Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of recipes. Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches. Written by one of the top biostatisticians in the field, Statistics for Epidemiology stands apart in its focus on interpretation and in the depth of understanding it provides. It lays the groundwork that all public health professionals, epidemiologists, and biostatisticians need to successfully design, conduct, and analyze epidemiological studies. |
| statistics for epidemiology: Statistics for Epidemiology Nicholas P. Jewell, 2003-08-26 Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of recipes.Statistics for E |
| statistics for epidemiology: Statistics in Epidemiology Hardeo Sahai, Anwer Khurshid, 1995-12-21 Epidemiologic studies provide research strategies for investigating public health and scientific questions relating to the factors that cause and prevent ailments in human populations. Statistics in Epidemiology: Methods, Techniques and Applications presents a comprehensive review of the wide range of principles, methods and techniques underlying prospective, retrospective and cross-sectional approaches to epidemiologic studies. Written for epidemiologists and other researchers without extensive backgrounds in statistics, this new book provides a clear and concise description of the statistical tools used in epidemiology. Emphasis is given to the application of these statistical tools, and examples are provided to illustrate direct methods for applying common statistical techniques in order to obtain solutions to problems. Statistics in Epidemiology: Methods, Techniques and Applications goes beyond the elementary material found in basic epidemiology and biostatistics books and provides a detailed account of techniques: |
| statistics for epidemiology: Basic Statistics and Epidemiology Antony Stewart, 2002 Most healthcare professionals need to be able to read and understand clinical evidence, and make a judgment on what treatments are effective. To do this, they need a basic grounding in statistics and epidemiology. This book aims to help readers by stimulating their interest and helping them understand the basics quickly and simply. |
| statistics for epidemiology: Statistical Methods for Global Health and Epidemiology Xinguang Chen, (Din) Ding-Geng Chen, 2020-04-13 This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health and epidemiology involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, cancer, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective; addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation. |
| statistics for epidemiology: Epidemiology and Medical Statistics , 2007-11-21 This volume, representing a compilation of authoritative reviews on a multitude of uses of statistics in epidemiology and medical statistics written by internationally renowned experts, is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. While the use of statistics in these fields has a long and rich history, explosive growth of science in general and clinical and epidemiological sciences in particular have gone through a see of change, spawning the development of new methods and innovative adaptations of standard methods. Since the literature is highly scattered, the Editors have undertaken this humble exercise to document a representative collection of topics of broad interest to diverse users. The volume spans a cross section of standard topics oriented toward users in the current evolving field, as well as special topics in much need which have more recent origins. This volume was prepared especially keeping the applied statisticians in mind, emphasizing applications-oriented methods and techniques, including references to appropriate software when relevant.· Contributors are internationally renowned experts in their respective areas· Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research· Methods for assessing Biomarkers, analysis of competing risks· Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs· Structural equations modelling and longitudinal data analysis |
| statistics for epidemiology: Modern Infectious Disease Epidemiology Alexander Krämer, Mirjam Kretzschmar, Klaus Krickeberg, 2010-01-23 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. |
| statistics for epidemiology: Biostatistics for Epidemiology and Public Health Using R Bertram K.C. Chan, PhD, 2015-11-05 Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-bystep approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems and exercises drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual. KEY FEATURES: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes online student solutions guide and instructor's manual |
| statistics for epidemiology: Spatial Analysis in Epidemiology Dirk U. Pfeiffer, Timothy P. Robinson, Mark Stevenson, Kim B. Stevens, David J. Rogers, Archie C. A. Clements, 2008-05-29 This book provides a practical, comprehensive and up-to-date overview of the use of spatial statistics in epidemiology - the study of the incidence and distribution of diseases. Used appropriately, spatial analytical methods in conjunction with GIS and remotely sensed data can provide significant insights into the biological patterns and processes that underlie disease transmission. In turn, these can be used to understand and predict disease prevalence. This user-friendly text brings together the specialised and widely-dispersed literature on spatial analysis to make these methodological tools accessible to epidemiologists for the first time. With its focus is on application rather than theory, Spatial Analysis in Epidemiology includes a wide range of examples taken from both medical (human) and veterinary (animal) disciplines, and describes both infectious diseases and non-infectious conditions. Furthermore, it provides worked examples of methodologies using a single data set from the same disease example throughout, and is structured to follow the logical sequence of description of spatial data, visualisation, exploration, modelling and decision support. This accessible text is aimed at graduate students and researchers dealing with spatial data in the fields of epidemiology (both medical and veterinary), ecology, zoology and parasitology, environmental science, geography and statistics. |
| statistics for epidemiology: Epidemiology Mark Woodward, 2013-12-19 Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems. New to the Third Edition New chapter on risk scores and clinical decision rules New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines Many more exercises and examples using both Stata and SAS More than 60 new figures After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding. Web Resource A wealth of supporting material can be downloaded from the book’s CRC Press web page, including: Real-life data sets used in the text SAS and Stata programs used for examples in the text SAS and Stata programs for special techniques covered Sample size spreadsheet |
| statistics for epidemiology: Clinical Epidemiology and Biostatistics Michael S. Kramer, 2012-12-06 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. |
| statistics for epidemiology: Multivariate Methods in Epidemiology Theodore R. Holford, 2002-05-30 This text describes the statistical tools that are currently used to analyse epidemiologic data on the association between possible risk factors and the actual risk of disease. |
| statistics for epidemiology: Modern Methods for Epidemiology Yu-Kang Tu, Darren C. Greenwood, 2012-05-22 Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology. |
| statistics for epidemiology: Statistical Epidemiology Graham R. Law, Shane W. Pascoe, 2013 Statistics are a vital skill for epidemiologists and form an essential part of clinical medicine. This textbook introduces students to statistical epidemiology methods in a carefully structured and accessible format with clearly defined learning outcomes and suggested chapter orders that can be tailored to the needs of students at both undergraduate and graduate level from a range of academic backgrounds. The book covers study design, disease measuring, bias, error, analysis and modelling and is illustrated with figures, focus boxes, study questions and examples applicable to everyday clinical problems. Drawing on the authors' extensive teaching experience, the text provides an introduction to core statistical epidemiology that will be a valuable resource for students and lecturers in health and medical sciences and applied statistics, health staff, clinical researchers and data managers. |
| statistics for epidemiology: Basic Biostatistics Gerstman, 2014-02-07 Basic Biostatistics is a concise, introductory text that covers biostatistical principles and focuses on the common types of data encountered in public health and biomedical fields. The text puts equal emphasis on exploratory and confirmatory statistical methods. Sampling, exploratory data analysis, estimation, hypothesis testing, and power and precision are covered through detailed, illustrative examples. The book is organized into three parts: Part I addresses basic concepts and techniques; Part II covers analytic techniques for quantitative response variables; and Part III covers techniques for categorical responses. The Second Edition offers many new exercises as well as an all new chapter on Poisson Random Variables and the Analysis of Rates. With language, examples, and exercises that are accessible to students with modest mathematical backgrounds, this is the perfect introductory biostatistics text for undergraduates and graduates in various fields of public health. Features: Illustrative, relevant examples and exercises incorporated throughout the book. Answers to odd-numbered exercises provided in the back of the book. (Instructors may requests answers to even-numbered exercises from the publisher. Chapters are intentionally brief and limited in scope to allow for flexibility in the order of coverage. Equal attention is given to manual calculations as well as the use of statistical software such as StaTable, SPSS, and WinPepi. Comprehensive Companion Website with Student and Instructor's Resources. |
| statistics for epidemiology: Essentials of Epidemiology in Public Health Ann Aschengrau, George R. Seage, 2013-06-03 5733-8 |
| statistics for epidemiology: Basic Concepts in Statistics and Epidemiology Theodore H. MacDonald, Denis Pereira Gray, 2018-10-08 This book contains a Foreword by Allyson Pollock, Professor and Head, Centre for International Public Health Policy, University of Edinburgh. Healthcare students, practitioners and researchers need a sound basis for making valid statistical inferences from health data. To make the best use of statistical software, it is necessary to understand how probabilistic inference works. This book explains that, along with the various ways statistical data can be described and presented. It is designed to develop insight rather than simply the mechanical skills found in other textbooks. This book is specifically designed to underpin the concepts of statistics and epidemiology. It is practical and easy to use and is ideal for people who can feel uncomfortable with mathematics. 'Excellent. A great primer for all students and research workers engaged in learning how to use statistical ideas in public health. It sets out the core concepts and explains them clearly, using worked examples as illustration. If followed carefully, the engaged reader should be able to use the standard statistical software packages intelligently and sensitively. It will stimulate the public health student, in whatever context, and new researchers, to approach the enterprise with enhanced confidence in interpreting and coherently explaining their findings.' - Allyson Pollock, in the Foreword. |
| statistics for epidemiology: Measurement Error and Misclassification in Statistics and Epidemiology Paul Gustafson, 2003-09-25 Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassi |
| statistics for epidemiology: Statistical Methods in Genetic Epidemiology Duncan C. Thomas, 2004-01-29 This balanced and well-integrated text gives a lucid overview of the entire process of genetic epidemiology, from familial aggregation through segregation, likage, and association studies. It is illustrated throughout with examples from the literature on cancer genetics. Statistical concepts are developed in depth, but with a focus on applications. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics are included. Oriented to graduate students in biostatistics, epidemiology, and human genetics, the book will also be a useful reference for researchers. It gives equal emphasis to study designs and data analysis. |
| statistics for epidemiology: Biostatistics and Epidemiology Sylvia Wassertheil-Smoller, 2013-06-29 Biostatistics and Epidemiology: A Primer for Health Professionals focuses on the underlying framework of the field and offers practical guidelines for research and interpretation. In addition to major sections devoted to statistics and epidemiology, the book includes a comprehensive exploration of the scientific method, probability, and clinical trials. New to the second edition are: -a reorganization of the material -new information on survival analysis such as the Cox proportional hazards model -topics in nonparametric statistics -expanded discussion of probability and its applications in epidemiology -an entirely new chapter on areas relevant to behavioral research and change scores, reliability, validity, and responsiveness -new appendices providing specific and clear instructions on how to carry out several additional statistical calculations and tests Biostatistics and Epidemiology describes principles and methods applicable to medicine, public health, allied health, psychology and education and will be useful not only to physicians doing clinical as well as basic science research, but also to students at undergraduate, graduate and medical school levels. |
| statistics for epidemiology: Statistical Methods in Epidemiology Harold A. Kahn, Christopher T. Sempos, 1989 This book is an expanded version of the Kahn's widely used text, An Introduction to Epidemiologic Methods (Oxford, 1983). It provides clear insight into the basic statistical tools used in epidemiology and is written so that those without advanced statistical training can comprehend the ideas underlying the analytical techniques. The authors emphasize the extent to which similar results are obtained from different methods, both simple and complex. To this edition they have added a new chapter on Comparison of Numerical Results for Various Methods of Adjustment and also one on The Primacy of Data Collection. New topics include the Kaplan-Meier product-limit method and the Cox proportional hazards model for analysis of time-related outcomes. An appendix of data from the Framingham Heart Study is used to illustrate the application of various analytical methods to an identical set of real data and provides source material for student exercises. The text has been updated throughout. |
| statistics for epidemiology: Foundations of Epidemiology Marit L. Bovbjerg, 2020-10 Foundations of Epidemiology is an open access, introductory epidemiology text intended for students and practitioners in public or allied health fields. It covers epidemiologic thinking, causality, incidence and prevalence, public health surveillance, epidemiologic study designs and why we care about which one is used, measures of association, random error and bias, confounding and effect modification, and screening. Concepts are illustrated with numerous examples drawn from contemporary and historical public health issues. |
| statistics for epidemiology: Quantitative Methods for Health Research Nigel Bruce, Daniel Pope, Debbi Stanistreet, 2013-03-18 Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community. Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts. The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so. The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation. |
| statistics for epidemiology: Encyclopedia of Epidemiology Sarah Boslaugh, 2008 Presents information from the field of epidemiology in a less technical, more accessible format. Covers major topics in epidemiology, from risk ratios to case-control studies to mediating and moderating variables, and more. Relevant topics from related fields such as biostatistics and health economics are also included. |
| statistics for epidemiology: An Introduction to Epidemiology for Health Professionals Jørn Olsen, Kaare Christensen, Jeff Murray, Anders Ekbom, 2010-06-14 Today, the public worries about emerging diseases and rapid changes of the frequency of well known diseases like autism, diabetes and obesity making the word epidemic part of the general discussion. Epidemiology should therefore be a basic component of medical training, yet often it is undertaught or even neglected. Concise and readable while also rigorous and thorough, An Introduction to Epidemiology for Health Professionals goes beyond standard textbook content to ground the reader in scientific methods most relevant to the current health landscape and the evolution of evidence-based medicine—valuable keys to better understanding of disease process, effective prevention, and targeted treatment. |
| statistics for epidemiology: Clinical Epidemiology Robert Fletcher, Suzanne W. Fletcher, Suzanne W Fletcher, MD, Msc, 2013-01-08 Now in its Fifth Edition, Clinical Epidemiology: The Essentials is a comprehensive, concise, and clinically oriented introduction to the subject of epidemiology. Written by expert educators, this text introduces students to the principles of evidence-based medicine that will help them develop and apply methods of clinical observation in order to form accurate conclusions. The Fifth Edition includes more complete coverage of systematic reviews and knowledge management, as well as other key topics such as abnormality, diagnosis, frequency and risk, prognosis, treatment, prevention, chance, studying cases and cause. |
| statistics for epidemiology: Fundamentals of Epidemiology and Biostatistics Ray M. Merrill, 2013 This book will familiarize your students with basic principles of epidemiology and biostatistics. Designed for use in a single course, it will clarify the distinction and complementary roles of epidemiology and biostatistics in a range of settings, and train students on the complementary roles epidemiology and biostatistics play in carrying out selected activities in the health professions. |
| statistics for epidemiology: Applications of Regression Models in Epidemiology Erick Suárez, Cynthia M. Pérez, Roberto Rivera, Melissa N. Martínez, 2017-02-13 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 SUÁREZ 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. PÉREZ 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. MARTÍNEZ 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. |
| statistics for epidemiology: Statistics in Medicine Robert H. Riffenburgh, Daniel L. Gillen, 2020-07-03 Statistics in Medicine, Fourth Edition, helps medical and biomedical investigators design and answer questions about analyzing and interpreting data and predicting the sample size required to achieve useful results. It makes medical statistics easy for the non-biostatistician by outlining common methods used in 90% of medical research. The text covers how to plan studies from conception to publication, what to do with data, and follows with step-by-step instructions for biostatistical methods from the simplest levels, to more sophisticated methods now used in medical articles. Examples from almost every medical specialty, and from dentistry, nursing, pharmacy and health care management are provided. This book does not require background knowledge of statistics or mathematics beyond high school algebra and provides abundant clinical examples and exercises to reinforce concepts. It is a valuable source for biomedical researchers, healthcare providers and anyone who conducts research or quality improvement projects. - Expands and revises important topics, such as basic concepts behind descriptive statistics and testing, descriptive statistics in three dimensions, the relationship between statistical testing and confidence intervals, and more - Presents an easy-to-follow format with medical examples, step-by-step methods and check-yourself exercises - Explains statistics for users with little statistical and mathematical background - Encompasses all research development stages, from conceiving a study, planning it in detail, carrying out the methods, putting obtained data in analyzable form, analyzing and interpreting the results, and publishing the study |
| statistics for epidemiology: Basic Epidemiology R. Bonita, R. Beaglehole, Tord Kjellström, World Health Organization, 2006 Basic epidemiology provides an introduction to the core principles and methods of epidemiology, with a special emphasis on public health applications in developing countries. This edition includes chapters on the nature and uses of epidemiology; the epidemiological approach to defining and measuring the occurrence of health-related states in populations; the strengths and limitations of epidemiological study designs; and the role of epidemiology in evaluating the effectiveness and efficiency of health care. The book has a particular emphasis on modifiable environmental factors and encourages the application of epidemiology to the prevention of disease and the promotion of health, including environmental and occupational health. |
| statistics for epidemiology: Biostatistics for Epidemiologists Anders Ahlbom, 2017-11-22 Biostatistics for Epidemiologists is a unique book that provides a collection of methods that can be used to analyze data in most epidemiological studies. It examines the theoretical background of the methods described and discusses general principles that apply to the analysis of epidemiological data. Specific topics addressed include statistical interference in epidemiological research, important methods used for analyzing epidemiological data, multivariate models, dose-response analysis, analysis of the interaction between causes of disease, meta-analysis, and computer programs. Biostatistics for Epidemiologists will be a useful guide for all epidemiologists and public health professionals who rely on biostatistical data in their work. |
| statistics for epidemiology: Epidemiology for Public Health Practice Robert H. Friis, Thomas A. Sellers, 2009 Review: Now in its Fourth Edition, this best-selling text offers comprehensive coverage of all the major topics in introductory epidemiology. With extensive treatment of the heart of epidemiology - from study designs to descriptive epidemiology to quantitative measures - this reader-friendly text is accessible and interesting to a wide range of beginning students in all health-related disciplines. A unique focus is given to real-world applications of epidemiology and the development of skills that students can apply in subsequent course work and in the field. The text is also accompanied by a complete package of instructor and student resources available through a companion Web site.--Jacket |
| statistics for epidemiology: Quantitative Epidemiology Xinguang Chen, 2022-02-22 This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis. |
| statistics for epidemiology: Epidemiology Rodolfo Saracci, 2010-02-25 What is epidemiology? What are the causes of a new disease? How can pandemics be prevented? Epidemiology is the study of the changing patterns of disease and its main aim is to improve the health of populations. It's a vital field, central to the health of society, to the identification of causes of disease, and to their management and prevention. Epidemiology has had an impact on many areas of medicine; from discovering the relationship between tobacco smoking and lung cancer, to the origin and spread of new epidemics. However, it is often poorly understood, largely due to misrepresentations in the media. In this Very Short Introduction Rodolfo Saracci dispels some of the myths surrounding the study of epidemiology. He provides a general explanation of the principles behind clinical trials, and explains the nature of basic statistics concerning disease. He also looks at the ethical and political issues related to obtaining and using information concerning patients, and trials involving placebos. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| statistics for epidemiology: Methods in Social Epidemiology J. Michael Oakes, Jay S. Kaufman, 2006-05-11 Social epidemiology is the study of how social interactions—social norms, laws, institutions, conventia, social conditions and behavior—affect the health of populations. This practical, comprehensive introduction to methods in social epidemiology is written by experts in the field. It is perfectly timed for the growth in interest among those in public health, community health, preventive medicine, sociology, political science, social work, and other areas of social research. Topics covered are: Introduction: Advancing Methods in Social Epidemiology The History of Methods of Social Epidemilogy to 1965 Indicators of Socioeconomic Position Measuring and Analyzing 'Race' Racism and Racial Discrimination Measuring Poverty Measuring Health Inequalities A Conceptual Framework for Measuring Segregation and its Association with Population Outcomes Measures of Residential Community Contexts Using Census Data to Approximate Neighborhood Effects Community-based Participatory Research: Rationale and Relevance for Social Epidemiology Network Methods in Social Epidemiology Identifying Social Interactions: A Review, Multilevel Studies Experimental Social Epidemiology: Controlled Community Trials Propensity Score Matching Methods for Social Epidemiology Natural Experiments and Instrumental Variable Analyses in Social Epidemiology and Using Causal Diagrams to Understand Common Problems in Social Epidemiology. Publication of this highly informative textbook clearly reflects the coming of age of many social epidemiology methods, the importance of which rests on their potential contribution to significantly improving the effectiveness of the population-based approach to prevention. This book should be of great interest not only to more advanced epidemiology students but also to epidemiologists in general, particularly those concerned with health policy and the translation of epidemiologic findings into public health practice. The cause of achieving a ‘more complete’ epidemiology envisaged by the editors has been significantly advanced by this excellent textbook. —Moyses Szklo, professor of epidemiology and editor-in-chief, American Journal of Epidemiology, Johns Hopkins University Social epidemiology is a comparatively new field of inquiry that seeks to describe and explain the social and geographic distribution of health and of the determinants of health. This book considers the major methodological challenges facing this important field. Its chapters, written by experts in a variety of disciplines, are most often authoritative, typically provocative, and often debatable, but always worth reading. —Stephen W. Raudenbush, Lewis-Sebring Distinguished Service Professor, Department of Sociology, University of Chicago The roadmap for a new generation of social epidemiologists. The publication of this treatise is a significant event in the history of the discipline. —Ichiro Kawachi, professor of social epidemiology, Department of Society, Human Development, and Health, Harvard University Methods in Social Epidemiology not only illuminates the difficult questions that future generations of social epidemiologists must ask, it also identifies the paths they must boldly travel in the pursuit of answers, if this exciting interdisciplinary science is to realize its full potential. This beautifully edited volume appears at just the right moment to exert a profound influence on the field. —Sherman A. James, Susan B. King Professor of Public Policy Studies, professor of Community and Family Medicine, professor of African-American Studies, Duke University |
| statistics for epidemiology: A Statistical Approach to Genetic Epidemiology Andreas Ziegler, Inke R. Kônig, Friedrich Pahlke, 2010-06-14 Diese zweite Auflage des sehr erfolgreichen Lehrbuchs der Statistik in der genetischen Epidemiologie wurde sorgfältig durchgesehen, aktualisiert und an vielen Stellen erweitert. Wie gewohnt mit vielen Aufgaben und Lösungen, dazu jetzt auch Farbabbildungen und auf Wunsch gekoppelt mit einem maßgeschneiderten E-Learning-Kurs. |
| statistics for epidemiology: Epidemiology, Biostatistics and Preventive Medicine James F. Jekel, David L. Katz, Dorothea Wild, Joann G. Elmore, 2007-05-18 Succinct yet thorough, Epidemiology, Biostatistics, and Preventive Medicine, 3rd Edition brings you today's best knowledge on epidemiology, biostatistics, preventive medicine, and public health-in one convenient source. You'll find the latest on healthcare policy and financing ? infectious diseases ? chronic disease ? and disease prevention technology. This text also serves as an outstanding resource for preparing for the USMLE, and the American Board of Preventive Medicine recommends it as a top review source for its core specialty examination. |
| statistics for epidemiology: Spatial Epidemiology Paul Elliott, 2000 Spatial epidemiology is concerned with describing, quantifying and explaining geographical variations in disease, especially with respect to variations in environmental exposures at the small-area scale. The recent and rapid expansion of the field looks set to continue in line with growing public, government and media concern about environment and health issues, and a scientific need to understand and explain the effects of environmental pollutants on health. This book brings together contributions from an international group of practitioners from a wide spectrum of disciplines including epidemiologists, statisticians, geographers, demographers and pollution modellers, providing a comprehensive reference on state-of-the-art methods and applications in the emerging field of spatial epidemiology. The book is divided into four sections. Section one gives an introduction to spatial epidemiological studies and summarises data requirements and problems with respect to modelling health events, including bias and confounding. Section two gives an overview of the state-of-the-art in statistical methodology, including Bayesian approaches to disease mapping, cluster detection, analysis of point exposures, geostatistical methods and methods for ecological correlation studies. Section three gives examples of disease mapping and cluster studies, involving mortality data, communicable disease data, Hodgkins disease, diabetes and childhood leukemias. Section four reviews methods ofexposure assessment for use in spatial epidemiological studies, and discusses possible links between exposure and health data in risk asessment, and in the effects on human health of traffic related pollution, water quality and climate change. This book aims to give an authoritative account of current practice and developments in the field. As such it should be of interest to epidemiologists, public health practitioners, statisticians, geographers, environmental scientists and others concerned with understanding the geographical distribution of disease and the effects of environmental exposures on human health. It will be a a valuable source for undergraduate and postgraduate coursees in epidemiology, medical geography, biostatistics, environmental health and environmental science as well as a useful source of reference for health policy makers, health economists, regulators and others in the field of environmental health. |
| statistics for epidemiology: An Introduction to Epidemiology Thomas C. Timmreck, 1998 Epidemiology/Biostatistics |
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