This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression. In addition, it considers special data structures like high-dimensional compositions and compositional tables. The methodology introduced is also frequently compared to methods which ignore the specific nature of compositional data. It focuses on practical aspects of compositional data analysis rather than on detailed theoretical derivations, thus issues like graphical visualization and preprocessing (treatment of missing values, zeros, outliers and similar artifacts) form an important part of the book. Since it is primarily intended for researchers and students from applied fields like geochemistry, chemometrics, biology and natural sciences, economics, and social sciences, all the proposed methods are accompanied by worked-out examples in R using the package robCompositions.

Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources. Bayesian Designs for Phase I-II Clinical Trials describes how phase I-II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory clinical trials. It illustrates many of the severe drawbacks with conventional methods used for early-phase clinical trials and presents numerous Bayesian designs for human clinical trials of new experimental treatment regimes. Written by research leaders from the University of Texas MD Anderson Cancer Center, this book shows how Bayesian designs for early-phase clinical trials can explore, refine, and optimize new experimental treatments. It emphasizes the importance of basing decisions on both efficacy and toxicity.

This is the third edition of this text on logistic regression methods, originally published in 1994, with its second e- tion published in 2002. As in the first two editions, each chapter contains a pres- tation of its topic in "lecture?book" format together with objectives, an outline, key formulae, practice exercises, and a test. The "lecture book" has a sequence of illust- tions, formulae, or summary statements in the left column of each page and a script (i. e. , text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This third edition has expanded the second edition by adding three new chapters and a modified computer appendix. We have also expanded our overview of mod- ing strategy guidelines in Chap. 6 to consider causal d- grams. The three new chapters are as follows: Chapter 8: Additional Modeling Strategy Issues Chapter 9: Assessing Goodness of Fit for Logistic Regression Chapter 10: Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves In adding these three chapters, we have moved Chaps. 8 through 13 from the second edition to follow the new chapters, so that these previous chapters have been ren- bered as Chaps. 11-16 in this third edition.

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.

Having last year published "Up from Clinical Epidemiology & EBM" and also "Epidemiological Research: Terms and Concepts," Miettinen now - this time with collaboration from his junior colleague I. Karp - brings out this further introduction into epidemiological research; and he is now working on an introduction into clinical research, for publication next year. It evidently is Miettinen's felt time to crystallize the basic understandings he has come to as the culmination of a half-century of concentrated effort to advance the theory of epidemiological and 'meta-epidemiological clinical' research.

In accord with its title, this book focuses on research to develop the knowledge-base for preventive medicine, which mainly is knowledge about the causal origin -etilogy, etiogenesis - of illness. It first illustrates how wanting this knowledge still is, despite much research; and it then aims to guide the reader to more productive etiogenetic research.

This book places much emphasis on the need to assure relevance by principles-guided objects design for the studies, which now remains conspicuously absent from epidemiologists' concerns. And as for methods design, this book exposes the fallacies in the still-common 'cohort' and 'case-control' studies, defines the essentials of all etiogenetic studies, and then addresses the true options for design in this framework of shared essentials.

A good deal of attention is also given to the still commonly-held, very major, twin fallacies that screening for an illness is a preventive intervention, to be studied by randomized trials, and that research on it can imply rational guidelines or recommendations regarding decisions about the screening.

While Miettinen already is regarded as 'the father of modern epidemiology, ' he now appears to have become the father also of post-modern epidemiology, where 'epidemiology' still means epidemiological research."

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it's more crucial than ever to know how well the healthcare system and all its components - from staff member to regional network - are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions. Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists. Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.

Identity theft, criminal investigations of the dead or missing, mass disasters both by natural causes and by criminal intent - with this as our day to day reality, the establishment and verification of human identity has never been more important or more prominent in our society. Maintaining and protecting the integrity of out identity has reached levels of unprecedented importance and has led to international legislation to protect our human rights.
Forensic Human Identification: An Introduction examines the variety of biological indicators that are available to investigators and illustrates the basic principles of each discipline. While DNA and fingerprints are clearly the favored methods of identification, they require a prior record and verifiable baseline for comparison. When these tools cannot be used it is necessary to employ those biological factors with higher variation and lower diagnostic probability. This reference introduces a number of different specialties such as, foot- and earprinting, dental interventions, skeletal anomalies, tattoos, facial reconstruction, personal effects, and handwriting.
While recognizing that no single factor is an absolute indicator of identity, the contributors explain how a multitude of factors taken into summative consideration can establish a probability for confirmation. They discuss the difference between positive and probable identification and the use of exclusion to confirm identity. Using three high profile case studies, the book addresses the context of human identification in today's society and illustrates the use of techniques described in the text.
Heavily referenced and using more than 120 charts, figures, photographs, and tables, Forensic Human Identification: An Introduction provides detailed introductory and extended information to newcomers and experts alike on the wide range of identification techniques in international practice.

Get Up to Speed on Many Types of Adaptive Designs Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials. New to the Second Edition Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials Twenty new SAS macros and R functions Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.

A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated second edition includes new and expanded content on avoiding common mistakes in meta-analysis, understanding heterogeneity in effects, publication bias, and more. Several brand-new chapters provide a systematic "how to" approach to performing and reporting a meta-analysis from start to finish. Written by four of the world's foremost authorities on all aspects of meta-analysis, the new edition: Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects models for synthesizing data Demonstrates how to assess and interpret variation in effect size across studies Explains how to avoid common mistakes in meta-analysis Discusses controversies in meta-analysis Includes access to a companion website containing videos, spreadsheets, data files, free software for prediction intervals, and step-by-step instructions for performing analyses using Comprehensive Meta-Analysis (CMA)(TM) Download videos, class materials, and worked examples at www.Introduction-to-Meta-Analysis.com This book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework. The authors address a series of common mistakes and explain how to avoid them. As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book. Harris Cooper, Hugo L. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the American Psychologist, former editor of Psychological Bulletin A superb combination of lucid prose and informative graphics, the authors provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students raved about the clarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics. The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice. Jesse A. Berlin, ScD This book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework. The authors address a series of common mistakes and explain how to avoid them. As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book. Harris Cooper, Hugo L. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the American Psychologist, former editor of Psychological Bulletin A superb combination of lucid prose and informative graphics, the authors provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students raved about the clarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics. The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice. Jesse A. Berl

Genetic Association Studies is designed for students of public health, epidemiology, and the health sciences, covering the main principles of molecular genetics, population genetics, medical genetics, epidemiology and statistics. It presents a balanced view of genetic associations with coverage of candidate gene studies as well as genome-wide association studies. All aspects of a genetic association study are included, from the lab to analysis and interpretation of results, but also bioinformatics approaches to causality assessment. The role of the environment in genetic disease is also highlighted. Genetic Association Studies will enable readers to understand and critique genetic association studies and set them on the way to designing, executing, analyzing, interpreting, and reporting their own.

Foodborne Diseases: Case Studies of Outbreaks in the Agri-Food Industries defines the context of foodborne disease across a range of food sectors. It provides insight into the causes and management of outbreaks along with practical lessons about foodborne disease prevention strategies relevant to stakeholders throughout the food supply chain. Individual chapters capture the epidemiological and traceback investigations of foodborne disease outbreaks in a wide range of food sectors that include fresh produce, dairy and eggs, and meat products, to complex food ingredients and products within the food manufacturing and food service sectors. Under each food category, case studies of real outbreaks are presented, along with lessons learned in the way they were managed for future control of foodborne disease outbreaks. The authors look at management of outbreaks across borders and consider how both local and international authorities dealt with the issues in each case. They focus on real-life microbiological/chemical-associated outbreaks and provide insights on how the outbreaks occurred and, if possible, how they were traced to the source of contamination. Each outbreak is unique, and readers are given the distinctive circumstances associated with different hazards, challenges faced during epidemiological and environmental investigations, risk communication to the general public, and insights into outbreak management. The authors cover the entire food supply chain, including a chapter on animal feed safety. A chapter on fraud and foodborne outbreaks considers scenarios where food industries, food services, and other stakeholders commit food adulteration, which ultimately leads to foodborne illnesses. Outbreak management and prevention strategies are key parts of each case study.

It was the ultimate test for CEOs, and almost none of them saw it coming. __________ In early March 2020, with the Dow Jones flirting with 30,000, the world's biggest companies were riding an eleven-year economic high. By the end of the month, millions would be out of work, iconic firms were begging for bailouts, and countless small businesses were in freefall. Slick consulting teams and country-club connections were suddenly of little use: business leaders were fumbling in the dark, tossing out long-term strategy and making decisions on the fly-decisions, they hoped, that might just save them. In Crash Landing, award-winning business journalist Liz Hoffman shows how the pandemic set the economy on fire-but if you look closely, the tinder was already there. Based on astonishing access inside some of the world's biggest and most iconic companies, this is a gripping account of the most remarkable period in modern economic history, revealing how they battled against an economic catastrophe for which there was no playbook: among them, AirBnB's Brian Chesky, blindsided by a virus in the middle of a high-stakes effort to go public; American Airlines's Doug Parker, shuttling between K Street and the White House, determined to secure a multi-billion-dollar bailout; and Ford's Jim Hackett, as his assembly lines went from churning out cars to ventilators. Crash Landing reveals the fear, grit, and gambles of the pandemic economy, while probing its implications for the future of work, corporate leadership, and capitalism itself, asking: Will this remarkable time give rise to newfound resilience, or become just another costly mistake to be forgotten? __________ A gripping account of the financial carnage of the pandemic, revealing the fear, grit, and gambles that drove the economy's winners and losers.

Health geographers are well situated for undertaking population health intervention research (PHIR), and have an opportunity to be at the forefront of this emerging area of inquiry. However, in order to advance PHIR, the scientific community needs to be innovative with its methodologies, theories, and ability to think critically about population health issues. For example, using alternatives (e.g. community-based participatory research) to traditional study designs such as the randomised control trial, health geographers can contribute in important ways to understanding the complex relationships between population health (both intended and unintended consequences), interventions and place. Representing a diverse array of health concerns ranging across chronic and infectious diseases, and research employing varied qualitative and quantitative methodologies, the contributions to this book illustrate how geographic concepts and approaches have informed the design and planning of intervention(s) and/or the evaluation of health impacts. For example, the authors argue that geographically targeting interventions to places of high-need and tailoring interventions to local place contexts are critically important for intervention success. Including an afterword by Professor Louise Potvin, this book will appeal to researchers interested in population and public/community health and epidemiology as well as health geography.

The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.

This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.

COVID-19: Surviving a Pandemic provides critical insights into survival strategies employed by communities and individuals around the world during the pandemic. A central question since this pandemic began has been how to survive it. That question has applied not just to staying alive, but also to staying healthy, both physically and mentally. Survival is certainly key, but surviving, and what that means, is also critical. The scholarship included in this volume will take a closer look at what it means to survive by addressing such issues as the importance of ethnicity in vaccine uptake, the gendered and racialized impacts of the pandemic, the impact on those with disabilities, questions of food security, and what it means to grieve. Drawing on the expertise of scholars from around the world, the work presented here represents a remarkable diversity and quality of impassioned scholarship on the impact of COVID-19 and is a timely and critical advance in knowledge related to the pandemic.

This volume elaborately studies the challenges posed and impact made by the Covid 19 pandemic. Through detailed case studies, it presents ethical, political, economic, medical, logistical and social impediments faced by contemporary states in the EU. The book focuses on the short and long-term consequences of the economic shock caused by the COVID-19 pandemic and covers issues concerning the world economy, the EU economy, as well as the Visegrad economies. The essays in this volume: Probes into the response of states to the economic phenomena resulting from the pandemic and analyses the institutional framework of the resulting crisis, lapses in social communication, social protests and the decline in democratic standards in countries such as the Czech Republic, Poland, Slovakia, and Hungary; Discusses issues related to state security under conditions of the pandemic, the effectiveness of state and self-government administration, the transition of states from an external controllability to an internal controllability model of power, as well as challenges related to security in the digital space; Presents policy actions at three basic levels, i.e. at the global, regional and sub-regional, and investigate strategies of the UN, WHO, the EU and the Visegrad Group as they play the most important role in the fight against COVID-19; This insightful and timely volume will be of great interest to scholars, researchers and anyone inquisitive about political theory, public policy, public health and social care, international relations, governance, security studies, and public administration.

A truly definitive work, this magisterial study draws on the latest evidence from across Europe to show in exhaustive detail the nature of the disease, its origin, spread, mortality, and its profound impact on history. The Black Death was a disaster of huge magnitude, shaking medieval Europe and beyond to its economic and social core. Building upon his acclaimed study of 2004, Ole Benedictow here draws upon new scholarship and research to present a comprehensive, definitive account of the Black Death and its impact on European history. The medical and epidemiological characteristics of the disease, its geographical origin, its spread across Asia Minor, the Middle East, North Africa, Europe and Russia, and the mortality in the countries and regions for which there are satisfactory studies, are clearly presented and thoroughly discussed. The pattern, pace and seasonality of the spread of the disease reflect current medical work and standard studies on the epidemiology of bubonic plague. Benedictow's findings make it clear that the true mortality rate was far higher than had been previously thought: some 60% of Europe's population. In the light of those findings, the discussion of the Black Death as a turning point in history takes on a new significance.

Presenting current research on spatial epidemiology, this book covers topics such as exposure, chronic disease, infectious disease, accessibility to health care settings and new methods in Geographical Information Science and Systems. For epidemiologists, and for the management and administration of health care settings, it is critical to understand the spatial dynamics of disease. For instance, it is crucial that hospital administrators develop an understanding of the flow of patients over time, especially during an outbreak of a particular disease, so they can plan for appropriate levels of staffing and to carry out adaptive prevention measures. Furthermore, understanding where and why a disease occurs at a certain geographic location is vital for decision makers to formulate policy to increase the accessibility to health services (either by prevention, or adding new facilities). Spatial epidemiology relies increasingly on new methodologies, such as clustering algorithms, visualization and space-time modelling, the domain of Geographic Information Science. Implementation of those techniques appears at an increasing pace in commercial Geographic Information Systems, alongside more traditional techniques that are already part of such systems. This book provides the latest methods in GI Science and their use in health related problems.

Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive randomization designs? Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects answers these questions and more. From novel designs to cutting-edge applications, this book presents several new and key developments in adaptive randomization. It also offers a fresh and critical look at a number of already-classical topics. Featuring contributions from statisticians, clinical trialists, and subject-matter experts in academia and the pharmaceutical industry, the text: Clarifies the taxonomy of the concept of adaptive randomization Discusses restricted, covariate-adaptive, response-adaptive, and covariate-adjusted response-adaptive (CARA) randomization designs, as well as randomized designs with treatment selection Gives an exposition to many novel adaptive randomization techniques such as brick tunnel randomization, targeted least absolute shrinkage and selection operator (LASSO)-based CARA randomization, multi-arm multi-stage (MAMS) designs, to name a few Addresses the issues of statistical inference following covariate-adaptive and response-adaptive randomization designs Describes a successful implementation of a single pivotal phase II/III adaptive trial in infants with proliferating hemangioma Explores some practical aspects of phase II dose-ranging studies and examines statistical monitoring and interim analysis issues in response-adaptive randomized clinical trials Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects covers a wide spectrum of topics related to adaptive randomization designs in contemporary clinical trials. The book provides a thorough exploration of the merits of adaptive randomization and aids in identifying when it is appropriate to apply such designs in practice.

This edited volume introduces the latest advances in quantitative methods and illustrates ways to apply these methods to important questions in substance use research. The goal is to provide a forum for dialogue between methodologists developing innovative multivariate statistical methods and substance use researchers who have produced rich data sets. Reflecting current research trends, the book examines the use of longitudinal techniques to measure processes of change over time. Researchers faced with the task of studying the causes, course, treatment, and prevention of substance use and abuse will find this volume helpful for applying these techniques to make optimal use of their data. This innovative volume: introduces the use of latent curve methods for describing individual trajectories of adolescent substance use over time; explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups; demonstrates how different patterns of missing data influence the interpretation of results; reports on some recent advances in longitudinal growth modeling; illustrates methods to assess mediation when there are multiple mediating pathways underlying an intervention effect; describes methods to identify moderating relations in structural equation models; demonstrates the use of structural equation models to evaluate a preventive intervention; applies epidemic modeling techniques to understand the spread of substance use in society; illustrates the use of latent transition analysis to model substance use as a series of stages; and applies logistic regression to prospectively predict smoking cessation.

Perinatal Epidemiology synthesizes perinatal knowledge through the lens of public health practice. This comprehensive text uses a consistent, logical format to offer readers: (1) A spectrum of topics affecting maternal and infant health: reproductive health concerns, maternal and infant morbidity and mortality, and gestation and fetal growth. (2) Information on timely issues, including infertility, gestational diabetes, preterm delivery, postpartum depression, and SIDS. (3) Detailed discussions of current epidemiological trends, measures and measurement issues, data sources, and risk and protective factors for each condition covered. (4) In-depth consideration of public health interventions and their availability, strengths and limitations. (5) Emerging areas of interest and directions for research. (6) Text boxes, definitions of key terms, discussion questions, appendices, and other helpful features.

Perinatal Epidemiology is a valuable, ready resource for public health professionals in maternal and child care, reproduction and fertility. Its accessibility and easy-use format make it an equally strong textbook for courses in these fields as well as for advanced medical and nursing students in OB/GYN and pediatrics.

A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. * Written in a clear, accessible style * Features real examples taken from the authors extensive practitioner experience of designing and analysing clinical trials * Demonstrates the use of R, Stata and SPSS for statistical analysis * Includes computer code so the reader can replicate all the analyses * Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.

'Understanding how complex ecological and climatic change can influence human health is the new challenge before us. The book confronts these multidimensional risk assessments head-on and will catalyse the important interdisciplinary and integrated approach that is the new paradigm now required for environmental and public health research.' Dr JONATHAN PATZ Johns Hopkins School of Hygiene and Public Health 'This book provides a sturdy foundation for thinking about how best to tackle a varied spectrum of population health hazards posed by different aspects and combinations of global change processes it alsogoes that extra mile by estimating the attributable population burdens of disease or mortality that are likely to result from these aspects of global change. It is heartening to see the results of this mathematical modeling being presented in policy-relevant terms.' From the Foreword by TONY McMICHAEL Health and Climate Change is the first major study of the potentially devastating health impacts of the global atmospheric changes which are under way. Using the best available data, the author presents models of the most plausible future courses of vector-borne diseases such as malaria, dengue fever and schistosomiasis; skin cancer caused by nozone depletion; and cardiovascular and respiratory disorders caused by higher temperatures. Current epidemiological research methods are not well adapted to analysing complex systems influenced by human intervention, or more simple processes calculated to take place within the distant future. Health and Climate Change proposes a new paradigm of integrated eco-epidemiological models for these areas of study. It will be essential reading for those concerned with public health and epidemiology, environmental studies, climate change and development studies. Originally published in 1998

Epidemiological criminology is an emerging paradigm which explores the public health outcomes associated with engagement in crime and criminal justice. This book engages with this new theory and practice-based discipline drawing on knowledge from criminology, criminal justice, public health, epidemiology, public policy, and law to illustrate how the merging of epidemiology into the field of criminology allows for the work of both disciplines to be more interdisciplinary, evidence-based, enriched and expansive. This book brings together an innovative group of exemplary researchers and practitioners to discuss applications and provide examples of epidemiological criminology. It is divided into three sections; the first explores the integration of epidemiology and criminology through theory and methods, the second section focuses on special populations in epidemiological criminology research and the role of race, ethnicity, age, gender and space as it plays out in health outcomes among offenders and victims of crime, and the final section explores the role policy and practice plays in worsening and improving the health outcomes among those engaged in the criminal justice system. Epidemiological Criminology is the first text to bring together, in one source, the existing interdisciplinary work of academics and professionals that merge the fields of criminology and criminal justice to public health and epidemiology. It will be of interest to academics and students in the fields of criminology, epidemiology, and public health, as well as clinical psychologists, law and government policy analysts and those working within the criminal justice system.