Modelling Survival Data in Medical Research, Fourth Edition describes the analysis of survival data, illustrated using a wide range of examples from biomedical research. Written in a non-technical style, it concentrates on how the techniques are used in practice. Starting with standard methods for summarising survival data, Cox regression and parametric modelling, the book covers many more advanced techniques, including interval-censoring, frailty modelling, competing risks, analysis of multiple events, and dependent censoring. This new edition contains chapters on Bayesian survival analysis and use of the R software. Earlier chapters have been extensively revised and expanded to add new material on several topics. These include methods for assessing the predictive ability of a model, joint models for longitudinal and survival data, and modern methods for the analysis of interval-censored survival data. Features: Presents an accessible account of a wide range of statistical methods for analysing survival data Contains practical guidance on modelling survival data from the author's many years of experience in teaching and consultancy Shows how Bayesian methods can be used to analyse survival data Includes details on how R can be used to carry out all the methods described, with guidance on the interpretation of the resulting output Contains many real data examples and additional data sets that can be used for coursework All data sets used are available in electronic format from the publisher's website Modelling Survival Data in Medical Research, Fourth Edition is an invaluable resource for statisticians in the pharmaceutical industry and biomedical research centres, research scientists and clinicians who are analysing their own data, and students following undergraduate or postgraduate courses in survival analysis.

This book is devoted to Corrado Gini, father of the Italian statistical school. It celebrates the 50th anniversary of his death by bearing witness to the continuing extraordinary scientific relevance of his interdisciplinary interests. The book comprises a selection of the papers presented at the conference of the Italian Statistical Society, Statistics and Demography - the Legacy of Corrado Gini, held in Treviso in September 2015. The work covers many topics linked to Gini's scientific legacy, ranging from the theory of statistical inference to multivariate statistical analysis, demography and sociology. In this volume, readers will find many interesting contributions on entropy measures, permutation procedures for the heterogeneity test, robust estimation of skew-normal parameters, S-weighted estimator, measures of multidimensional performance using Gini's delta, small-sample confidence intervals for Gini's gamma index, Bayesian estimation of the Gini-Simpson index, spatial residential patterns of selected foreign groups, minority segregation processes, dynamic time warping to study cruise tourism, and financial stress spill over. This book will appeal to all statisticians, demographers, economists, and sociologists interested in the field.

The book Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health presents the use of geospatial techniques to address a number of environmental issues, including land use change, climatic variability, urban sprawl, population density modelling, flooding, environmental health, water quality, energy resources, urban growth modelling, infectious diseases and the quality of life. Although the work is focused on the Megacity of Dhaka in Bangladesh, the techniques and methods that are used to research these issues can be utilized in any other areas where rapid population growth coupled with unplanned urbanization is leading to environmental degradation. The book is useful for people working in the area of Geospatial Science, Urban Geography, Environmental Management and International Development. Since the chapters in the book cover a range of environmental issues, this book describes useful tools for assisting informed decision making, particularly in developing countries.

First published in 1889, this book provides a guide to vital statistics- the science of numbers applied to the life-history of communities and nations- in relation to medical problems. Chapters cover a wide variety of categories including population, births and deaths, sickness, occupation and mortality, and mortality from special diseases.

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.

How can the various indicators of health, available through vital statistics, government publications, private surveys and other sources, be measured? This and other questions are brought to light in James Larson's important study of concepts in the health measurement of individuals and populations. This book is intended to provide a backdrop for future research into determining health care needs, while allowing for more efficient allocation of scarce resources by planners and administrators. The first chapter defines health by using five models, the two major ones being the medical and the holistic. The medical model is the absence of disease and disability, and the holistic generally defines health as physical, mental, and social well-being. Chapters two and three discuss the statistical measurement of mortality and morbidity (illness or disability) by government and other agencies. International health measurement is the focus of the fourth chapter, which includes descriptions of World Health Organization activities in planning for health impovements worldwide and the lack of accurate health measurement in developing countries. Chapter five discusses United States national health statistics gathering, while chapter six analyzes the less sophisticated vital statistics methodologies used at the state and local levels. In the final chapter, Larson proposes indicators for international, national, state, and local levels, given the best possible data for health measurement. The Measurement of Health will be of great value to health statisticians, scholars interested in health policy, students in courses concerning research methods in health, health services administrators, and health proessionals.

Examines the advent, during the mid-nineteenth century in Britain, of techniques of infectious disease surveillance, now one of the most powerful sets of tools in modern public health. Intrusive Interventions is a history and critical study of public health in the Victorian and Edwardian period. Drawing on an array of archival sources from across provincial England and London, it investigates the emergence and consolidation of a set of government policies that came to be known as infectious disease surveillance, including compulsory infectious disease notification, domestic quarantine, mandatory removal to a hospital, contact tracing, and the disinfection of homes and belongings. Although these were a set of spatialized practices implemented in diverse settings such as hospitals, schools, and disinfecting stations, their effect was to retrain the gaze of public health onto domestic space and in the process both disrupt and reinforce the centrality of the family and domesticity in Victorian and Edwardian culture. Examining political ideologies of freedom and individuality as well associal policy, medical theory, laboratory research, material culture, and public health practice, author Graham Mooney argues that infectious disease surveillance reconfigured late nineteenth-century hygienic norms and forms of citizenship. Public health practice had to be continually reshaped in order to negate the political fallout of a tendency toward coercion and unwanted interference -- debates that, as the author of this important study points out,continue to resonate today. Graham Mooney is Assistant Professor at the Institute of the History of Medicine, Johns Hopkins University.

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.

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."

This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas.

Despite adults' best preventive efforts, childhood obesity is on the rise in most areas of the world, and with it the prevalence of Type 2 diabetes, hypertension, cardiovascular disease, and other formerly adult-onset conditions. Epidemiology of Obesity in Children and Adolescents takes the global ecological approach that is needed to understand the scope of the problem and its multiple causes and mechanisms, and to aid in developing more effective prevention and intervention programs. In the book's first half, experts present a descriptive summary of youth obesity trends in ten world regions, broken down by age group, gender, socioeconomic status, and risk factors. Complementing these findings, part two reviews the evidence base regarding the variables, separately and in combination, having the most significant impact on young people's development of obesity, including: * Genetic and nutrigenomic factors. * Environmental and psychosocial factors, such as family shopping and eating habits and access to healthful foods. * Neuroendocrine regulation. * Prenatal and neonatal factors (e.g., gestational diabetes of the mother). * Dietary factors, from nutrient content to young people's food preferences. * Physical activity versus sedentary behavior. Epidemiology of Obesity in Children and Adolescents is necessary reading for the range of professionals involved in curtailing this epidemic, including public health specialists, epidemiologists, pediatricians, nurses, nutritionists, psychologists, health educators, and policymakers.

This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed to ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this second volume, Volume 126, covers research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. Contributions motivated by the study of diseases like influenza, HIV, tuberculosis, and macroparasitic like schistosomiasis are also included. This second volume requires additional mathematical sophistication, and graduate students in applied mathematics, scientists in the natural, social, and health sciences, or mathematicians who want to enter the field of mathematical and theoretical epidemiology will find it useful. The collection of contributors includes many who have been in the forefront of the development of the subject.

Multiple Sclerosis continues to be one of the most baffling and destructive diseases of our time, disabling a multitude of people around the globe. For researchers in various disciplines who are concerned with readily locating published data that are relevant to the sociodemographic factors in the epidemiology of MS, this volume makes accessible subject topics that focus on the demographic, sociocultural, and methodological correlates of the disease. Compiler George W. Lowis has gathered four decades of published research findings into this unique and useful volume. He provides summaries of 213 projects grouped according to whether they could possibly be implicated, either positively or negatively, as determinants of MS prevalence or incidence. Summaries of 192 projects look at 11 different demographic and sociocultural correlates of MS such as diet, ethnicity, urban-rural residence, and more. An additional 21 projects focus on the methodology or case ascertainment used. The majority of sample projects were abstracted from medical literature published in journals and books since 1960. Each project has been edited and presented in such a way that the author's purpose for conducting the research is made explicit, as are the main findings and conclusion. Divided into two parts, the volume first zeroes in on the sociodemographic projects. Included in the eleven chapters of this section are the demographic factors that may be implicated in MS such as age, sex, ethnicity, occupation, place of birth or residence, and population migration. Etiological factors in the sociocultural part of the environment include such variables as the types of social relationships and patterns of living that characterize people of different sexes, ages, races, and social classes and the ideas, values, and norms possessed and used by people in matters such as diet and nutrition, sanitation, and pet ownership. The second section reviews methodologic projects from the point of view of data collection and case ascertainment techniques used. Each of the 213 projects contains five sets of research information: a discussion of the purpose and occasionally the locale of the study; data relevant to the population studied; a report on the findings of the project; a brief concluding summary; and finally, an overview of other factors positively or negatively implicated. As the only book that approaches the epidemiology of MS with this focus, this annotated bibliography will be a tool of inestimable value to researchers in the fields of medical sociology, epidemiology, social epidemiology, public health, environmental health, and medical anthropology.

This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty.Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods.Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software.Illustrated throughout with computer examples in R.Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area.Examples in SAS and Stata for the most common situations are also provided.Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject.

Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed to ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this first volume, Volume 125, covers tutorial and research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. The volume includes the study of cancer, HIV, pertussis, and tuberculosis. Beginning graduate students in applied mathematics, scientists in the natural, social, or health sciences or mathematicians who want to enter the fields of mathematical and theoretical epidemiology will find this book useful.

This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel's first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.

Although medicine and sanitation in modernized countries are more advanced than ever before, over the past three decades we have seen the emergence of some 30 new diseases, such as HIV, SARS and Ebola. Lyme Disease, hepatitis C, Legionnaires' Disease and even Jacob-Creutzfeld, the human form of a disorder we know as "Mad Cow," have made headlines. We are also facing a resurgence of diseases once thought nearly eradicated, including tuberculosis and smallpox, and the persistence of rare disorders such as leprosy. In this work, Dr. Link explains the extent of new, resurgent, and resistant diseases defying the abilities of science and medicine, or often finding strength in globalization or other facets of modernization. Link also explains why such diseases are not prevented by our current systems, and why some rare diseases persist despite technology that could cure them. He offers insight into why we may not be able to predict or prevent factors such as mutations, and also shares thoughts about what we can do--as individuals, communities and countries--to reduce the dangers of disease. Including a basic review of elements that cause them--viruses, bacteria, parasites, and fungi among them--this work gives a brief history of human diseases and points out how the burden of disease has increased throughout the history of mankind. Diseases addressed in this book include, but are not limited to: BLMad Cow BLTuberculosis BLRabies BLSARS BLEbola BLLeprosy BLSmallpox BLDracunculiasis BLRingworm BLMalaria

This book provides a complete and current overview of the correlation between ocean conditions and human health, publishing comprehensively for the first time on the direct interactions among oceanography, marine biology and impacts on human health. Specifically the text addresses how changing ocean conditions result in health impacts and disruptions, with a focus on cases in the USA. The changing ocean conditions that are discussed include diminishing marine biodiversity, climactic changes such as intensified weather events, shifting sea currents and increasing sea temperature. The book addresses the resulting health issues brought about by these various ocean conditions, such as emerging infectious diseases, starvation and poisoning among impacted communities, toxic algae blooms, threatened ecosystems, and other future implications. The text was developed in conjunction with scientists from Brown University, the University of Rhode Island, the University of Texas at Austin, the University of California at Riverside and Ochsner Health, all located in areas deeply impacted by the changing Oceans. The book will be of interest to marine research scientists, health care professionals, students, and general enthusiasts of oceanography and health.

This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

It is a truism among biologists that an organism's phenotype is the product of both its genotype and its environment. An organism's genotype contains the total informational potential of the individual, while its environment shapes the expression of the ge- type, influences the rate of mutation and occurrence of modifications, and ultimately determines the likelihood that the genotype (or fractions thereof) will survive into the next generation. In the relationship between host and pathogen, therefore, each forms a part of the environment of the other, mutually influencing the biology of both partners on scales ranging from the life history of individuals to the fate of populations or entire species. Molecular biologists working on problems in pathogenesis generally think of the host organism as the pathogen's environment and perhaps occasionally consider the pathogen as part of the host's environment. However, because "environment" can be defined at many scales, so, too, can phenotypes: if a pathogen, as a species, is c- sidered to exist in a host, as a species, then among its phenotypes is the nature of the pandemic disease it can cause within the host community. The contributors to the proceedings of this NATO Advanced Research Workshop have treated the interplay of environment and genotype in the host-pathogen relationship and its relationship to the problem of emerging infectious disease at both the macroscopic and microscopic/ molecular levels along this continuum of scale (with some human history thrown in at times for good measure).

"Methods of Clinical Epidemiology" serves as a text on methods useful to clinical researchers. It provides a clear introduction to the common research methodology specific to clinical research for both students and researchers. This book sets out to fill the gap left by texts that concentrate on public health epidemiology and focuses on what is not covered well in such texts. The four sections cover methods that have not previously been brought together in one text and serves as a second level textbook of clinical epidemiology methodology. This book will be of use to postgraduate students in clinical epidemiology as well as clinical researchers at the start of their careers.

In recent decades radiobiologists' efforts have been directed at identifying the mechanisms of radiation effects; the general mechanisms have since been studied extensively. This book describes and analyzes radiation-induced adaptation as processes produced in cells, tissues, and populations. This viewpoint helps to understand the nature and factors of induced processes, to determine the characteristics of observed radiation effects and their limitations. The investigations presented here were founded on proper lab experiments, ecological studies of plant population growth near an operating nuclear power plant and a thorough epidemiological examination of human populations living in territories polluted fifty years ago, as well as on relevant published data. This research demonstrates the radiation-induced adaptation processes that continue even when the radiation itself is no longer at a critical background level. The investigations utilized the method of statistical modeling on the basis of distributions on the number of abnormalities. This method allows us to investigate the processes induced by low-dose factors when accompanied by Darwinian selection in different systems; the distribution parameters can then be used to study the characteristics of adaptation processes and system resistance. The consequences of background-level radiation continue to provoke debate, and the mathematical bases of the adaptation model are shown, while due consideration is paid to the components of adaptation: instability, selection, and proliferation. The book will be especially useful to specialists in radiation pollution, ecology, epidemiology, and radiology for studies of radiation-induced processes; the method presented here can also be adapted to investigate low-dose effects in other fields. In addition, the book presents a number of reviews in the fields of radiation biology, including pioneering investigations in Russia which were previously unavailable to Western scientists.

This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.

Plasma decontamination is a rapidly expanding area of modern science and engineering. An increasing number of engineers are using plasma methods for decontamination of chemical and biological agents. Plasma decontamination is effectively applied today to clean and sterilize different surfaces, high volume air and water streams, industrial exhausts, and even living tissue of animals and humans. This book provides a fundamental introduction to virtually all aspects of modern plasma decontamination, as well as the most recent technological achievements in the area.

The book is segmented into four specific sections of modern plasma decontamination: (1) plasma bio-decontamination, including disinfection and sterilization of surfaces, water and air streams; (2) plasma decontamination of chemical agents, including cleaning of air, water, and industrial exhaust gases from different pollutants and especially volatile organic compounds VOC; (3) plasma treatment of living tissue, including different subjects of plasma medicine from skin sterilization to tissue engineering; (4) major electric discharges applied for the plasma-assisted decontamination of chemical and biological agents.