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
This straightforward primer in basic statistics emphasises its practical use in epidemiology and public health, providing an understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research. This new Edition includes fresh sections on Correlation and Linear Regression, as well as brand new exercises reflecting current working life. Clearly worded and assuming no prior knowledge, it gives full step-by-step guidance on performing statistical calculations.Illustrated by numerous examples, and containing exercises with detailed answers, it will help readers grasp the main points of these complex subjects with ease.
The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch. The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field. Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research. Contents:Statistics in Medicine and Epidemiology:History of Statistical Thinking in Medicine (Tar Timothy Chen)Describing Data, Modeling Variation, and Statistical Practice (Hongyan Du and Ming T Tan)Covariate-Specific and Covariate-Adjusted Predictive Values of Prognostic Biomarkers with Survival Outcome (Yunbei Ma, Xiao-Hua Zhou and Kwun Chuen (Gary) Chan)Statistical Methods for Personalized Medicine (Lu Tian and Xiaoguang Zhao)Statistics Used in Quality Control, Quality Assurance, and Quality Improvement in Radiological Studies (Ying Lu and Shoujun Zhao)Applications of Statistical Methods in Medical Imaging (Jesse S Jin)Cost-Effectiveness Analysis and Evidence-Based Medicine (Jianli Li)Quality of Life: Issues Concerning Assessment and Analysis (Jiqian Fang and Yuantao Hao)Meta-Analysis (Xuyu Zhou, Jiqian Fang, Chuanhua Yu, Zongli Xu, Lu Tian, and Ying Lu)Statistical Models and Methods in Infectious Diseases (Hulin Wu and Shoujun Zhao)Special Models for Sampling Survey (Sujuan Gao)The Use of Capture–Recapture Methodology in Epidemiological Surveillance and Ecological Surveys (Anne Chao, T C Hsieh and Hsin-Chou Yang)Statistical Methods in the Effective Evaluation of Mass Screening for Diseases (Qing Liu)Statistics in Clinical Trials:Statistics in Biopharmaceutical Research and Development (Shein-Chung Chow and Annpey Pong)Statistics in Pharmacology and Pre-Clinical Studies (Tze Leung Lai, Mei-Chiung Shin and Guangrui Zhu)Statistics in Toxicology (James J Chen)Dose-Response Modeling and Benchmark Doses in Health Risk Assessment (Yiliang Zhu)Some Fundamental Statistical Issues and Methodologies in Confirmatory Trials (George Y H Chi, Haiyan Xu and Qing Liu)Surrogates for Qualitative Evaluation of Treatment Effects (Zhi Geng)Adaptive Trial Design in Clinical Research (Annpey Pong and Shein-Chung Chow)Statistics in the Research of Traditional Chinese Medicine (Danhui Yi and Yang Li)Statistical Genetics:Sparse Segment Identifications with Applications to DNA Copy Number Variation Analysis (X Jessie Jeng, T Tony Cai and Hongzhe Li)Statistical Methods for Design and Analysis of Linkage Studies (Qizhai Li, Hong Qin, Zhaohai Li, and Gang Zheng)Transcriptome Analysis Using Next-Generation Sequencing (Jingyi Jessica Li, Haiyan Huang, Minping Qian and Xuegong Zhang)Genetic Structure of Human Population (Hua Tang and Kun Tang)Data Integration Methods in Genome Wide Association Studies (Ning Sun and Hongyu Zhao)Causal Inference (Zhi Geng)General Methods:Survival Analysis (D Y Lin)Nonparametric Regression Models for the Analysis of Longitudinal Data (Colin O Wu, Xin Tian, Kai F Yu, and Mi-Xia Wu)Local Modeling: Density Estimation and Nonparametric Regression (Jianqing Fan and Runze Li)Statistical Methods for Dependent Data (Feng Chen)Bayesian Methods (Ming-Hui Chen and Keying Ye)Valid Prior-Free Probabilistic Inference and Its Applications in Medical Statistics (Duncan Ermini Leaf, Hyokun Yun, and Chuanhai Liu)Stochastic Processes and Their Applications in Medical Science (Caixia Li and Jiqian Fang)Interpolation of Missing Values and Adjustment of Moving Holiday Effect in Time Series (Zhang Jin-Xin, Zhang Xi, Xue Yun-Lian, Li Ji-Bin and Huang Bo)Tree-based Methods (Heping Zhang)Introduction to Artificial Neural Networks (Xia Jielai, Jiang Hongwei, and Tang Qiyi) Readership: Biostatisticians, applied statisticians, medical researchers and clinicians, biopharmaceutical researchers, public health epidemiologists, biometricians and applied mathematicians. Key Features: The book covers very broad topics in medical statistics The book covers both most recent developments as well as classical work of the selected areas The book chapter is written by the experts in the field and illustrated with real life examplesKeywords:Medicine;Statistics;Epidemiology;Genomics;Clinical Trials;Bioinformatics;Machine Learning;Statistical Theory;Public HealthReviews: Review of the First Edition: “Overall the book covers a wide variety of applications. Each method is presented in sufficient depth to allow the reader to understand when the method(s) can be used … this book would be a useful resource for any practitioner in medical research.” Statistical Methods in Medical Research
There has been a growing recognition of the importance of mathematical and statistical methods in the history of medicine, particularly in those areas where statistical methods are a sine qua non such as epidemiology and randomised clinical trials. Despite this expanding scholarly interest, the development of the mathematical and statistical technologies in the biological sciences has not been examined systematically. This collection of essays aims to provide a broader overview of this field, and to explore the use of these with the use of these quantitative technologies in medical and clinical cultures from the seventeenth to the twentieth centuries.
Medical Statistics at a Glance is a concise and accessible introduction and revision aid for this complex subject. The self-contained chapters explain the underlying concepts of medical statistics and provide a guide to the most commonly used statistical procedures. This new edition of Medical Statistics at a Glance: Presents key facts accompanied by clear and informative tables and diagrams Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of computer data analysis rather than complex hand calculations Includes extensive cross-referencing, a comprehensive glossary of terms and flow-charts to make it easier to choose appropriate tests Now provides the learning objectives for each chapter Includes a new chapter on Developing Prognostic Scores Includes new or expanded material on study management, multi-centre studies, sequential trials, bias and different methods to remove confounding in observational studies, multiple comparisons, ROC curves and checking assumptions in a logistic regression analysis The companion website at www.medstatsaag.com contains supplementary material including an extensive reference list and multiple choice questions (MCQs) with interactive answers for self-assessment. Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines. Reviews of the previous editions "The more familiar I have become with this book, the more I appreciate the clear presentation and unthreatening prose. It is now a valuable companion to my formal statistics course." –International Journal of Epidemiology "I heartily recommend it, especially to first years, but it's equally appropriate for an intercalated BSc or Postgraduate research. If statistics give you headaches - buy it. If statistics are all you think about - buy it." –GKT Gazette "...I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book." –4th Year Medical Student, Barts and the London Chronicle, Spring 2003
Social epidemiology is the study of how socialinteractions—social norms, laws, institutions, conventia,social conditions and behavior—affect the health ofpopulations. This practical, comprehensive introduction to methodsin social epidemiology is written by experts in the field. It isperfectly timed for the growth in interest among those in publichealth, community health, preventive medicine, sociology, politicalscience, 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 itsAssociation with Population Outcomes Measures of Residential Community Contexts Using Census Data to Approximate Neighborhood Effects Community-based Participatory Research: Rationale and Relevancefor Social Epidemiology Network Methods in Social Epidemiology Identifying Social Interactions: A Review, MultilevelStudies Experimental Social Epidemiology: Controlled CommunityTrials Propensity Score Matching Methods for Social Epidemiology Natural Experiments and Instrumental Variable Analyses inSocial Epidemiology and Using Causal Diagrams to Understand Common Problems inSocial Epidemiology. "Publication of this highly informative textbook clearlyreflects the coming of age of many social epidemiology methods, theimportance of which rests on their potential contribution tosignificantly improving the effectiveness of the population-basedapproach to prevention. This book should be of great interest notonly to more advanced epidemiology students but also toepidemiologists in general, particularly those concerned withhealth policy and the translation of epidemiologic findings intopublic health practice. The cause of achieving a ‘morecomplete’ epidemiology envisaged by the editors has beensignificantly advanced by this excellent textbook." —Moyses Szklo, professor of epidemiology andeditor-in-chief, American Journal of Epidemiology, JohnsHopkins University "Social epidemiology is a comparatively new field of inquirythat seeks to describe and explain the social and geographicdistribution of health and of the determinants of health. This bookconsiders the major methodological challenges facing this importantfield. Its chapters, written by experts in a variety ofdisciplines, are most often authoritative, typically provocative,and often debatable, but always worth reading." —Stephen W. Raudenbush, Lewis-Sebring DistinguishedService Professor, Department of Sociology, University ofChicago "The roadmap for a new generation of social epidemiologists. Thepublication of this treatise is a significant event in the historyof the discipline." —Ichiro Kawachi, professor of social epidemiology,Department of Society, Human Development, and Health, HarvardUniversity "Methods in Social Epidemiology not only illuminates thedifficult questions that future generations of socialepidemiologists must ask, it also identifies the paths they mustboldly travel in the pursuit of answers, if this excitinginterdisciplinary science is to realize its full potential. Thisbeautifully edited volume appears at just the right moment to exerta profound influence on the field." —Sherman A. James, Susan B. King Professor of PublicPolicy Studies, professor of Community and Family Medicine,professor of African-American Studies, Duke University
Translating the evidence from the bedside topopulations This sixth edition of the best-selling Epidemiology,Evidence-based Medicine and Public Health Lecture Notes equipsstudents and health professionals with the basic tools required tolearn, practice and teach epidemiology and health prevention in acontemporary setting. The first section, ‘Epidemiology’, introduces thefundamental principles and scientific basis behind work to improvethe health of populations, including a new chapter on geneticepidemiology. Applying the current and best scientific evidence totreatment at both individual and population level is intrinsicallylinked to epidemiology and public health, and has been introducedin a brand new second section: ‘Evidence-basedMedicine’ (EBM), with advice on how to incorporate EBMprinciples into your own practice. The third section, 'PublicHealth', introduces students to public health practice, includingstrategies and tools used to prevent disease, prolong life, reduceinequalities, and includes global health. Thoroughly updated throughout, including new studies and casesfrom around the globe, key learning features include: Learning objectives and key points in every chapter Extended coverage of critical appraisal and datainterpretation A brand new self-assessment section of SAQs and’True/False’ questions for each topic A glossary to quickly identify the meaning of key terms, all ofwhich are highlighted for study and exam preparation Further reading suggestions on each topic Whether approaching these topics for the first time, starting aspecial study module or placement, or looking for a quick-referencesummary, this book offers medical students, junior doctors, andpublic health students an invaluable collection of theoretical andpractical information.
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:
High-YieldTM Biostatistics, Epidemiology, and Public Health, Fourth Edition provides a concise review of the biostatistics concepts that are tested in the USMLE Step 1. Information is presented in an easy-to-follow format, with High-Yield Points that help students focus on the most important USMLE Step 1 facts. The High-YieldTM outline format, with tables, diagrams, photographs, and images to clarify important material, provides a concentrated, efficient review for both course exams and the USMLE.