Do you want to know what a parametric test is and when not to perform one? Do you get confused between odds ratios and relative risks? Want to understand the difference between sensitivity and specificity? Would like to find out what the fuss is about Bayes' theorem? Then this book is for you! Physicians need to understand the principles behind medical statistics. They don't need to learn the formula. The software knows it already! This book explains the fundamental concepts of medical statistics so that the learner will become confident in performing the most commonly used statistical tests. Each chapter is rich in anecdotes, illustrations, questions, and answers. Not enough? There is more material online with links to free statistical software, webpages, multimedia content, a practice dataset to get hands-on with data analysis, and a Single Best Answer questionnaire for the exam.

Fundamentals of Genetic Epidemiology meets the need for a sophisticated approach to the investigation of the causes of complex chronic diseases. This integrated text describes the principles, methods, and approaches of epidemiology and genetics in the study of disease etiology. It provides an historical overview of genetics and epidemiology and their gradual rapprochement, describing the fundamental research strategies of genetic epidemiology including population and family studies. The authors also illustrate the increasing importance of genetic epidemiology in its application to preventive medicine, public health surveillance and the emerging ethical issues regarding the use of genetic information in society.

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.

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.

Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient information to optimize that patient's health care, particularly in managing chronic conditions and treating cancer. In the statistical literature, sequential decision making is known as an adaptive treatment strategy (ATS) or a dynamic treatment regime (DTR). The field of DTRs emerges at the interface of statistics, machine learning, and biomedical science to provide a data-driven framework for precision medicine. The authors provide a learning-by-seeing approach to the development of ATSs, aimed at a broad audience of health researchers. All estimation procedures used are described in sufficient heuristic and technical detail so that less quantitative readers can understand the broad principles underlying the approaches. At the same time, more quantitative readers can implement these practices. This book:* Provides the most up-to-date summary of the current state of the statistical research in personalized medicine.* Contains chapters by leaders in the area from both the statistics and computer sciences fields.* Contains a range of practical advice, introductory and expository materials, and case studies.

-Written by the authors of key spatial R packages -Makes spatial data analysis more robust -Integrates with the tidyverse and comparable approaches -Includes many easily reproducible examples

Between August 1918 and March 1919 a flu pandemic spread across the globe and in just under a year 40 million people had died from the virus worldwide. This is the first book to provide a total history and seriously analyze the British experiences during that time. The book provides the most up-to-date tally of the pandemic's impact, including the vast mortality, as well as questioning the apparent origins of the pandemic. A 'total' history, this book ranges from the spread of the 1918-1919 pandemic, to the basic biology of influenza, and how epidemics and pandemics are possible, to consider the demographic, social, economic and political impacts of such a massive pandemic, including the cultural dimensions of naming, blame, metaphors, memory, the media, art and literature. An inter-disciplinary study, it stretches from history and geography through to medicine in order to convey the full magnitude of the first global medical 'disaster' of the twentieth century, and looks ahead to possible pandemics of the future. Niall Johnson brings an impressive scholarly eye on this fascinating and highly relevant topic making this essential reading for historians and those with an interest in British and medical history.

Epidemiology has long played a critical role in investigating outbreaks of foodborne illness and in identifying the microbial pathogens associated with such illness. Epidemiologists were the detectives who would track down the guilty culprit- the food vehicle carrying the pathogen, as well as the fateful errors that resulted in contamination or multiplication of pathogens. The first book of its kind, this volume describes the various ways epidemiologic principles are applied to meet the challenges of maintaining a safe food supply. It addresses both the prevention and control of food borne illness. Starting with a history and background of food borne illness, the book continues by describing the means of following up on an outbreak and measuring exposures. The book concludes by describing the regulatory context that shapes food safety activities at the local, national and international levels. Chapters are written by leaders in the field of public health and food safety, including experts in epidemiology, microbiology, risk assessment, economics, and environmental health and policy. This is the definitive book for students, researchers and professionals interested in how epidemiology plays a role in keeping our food safe.

This book makes an original contribution in addressing contemporary critical discussions and reflections on international health policies, strategies, programmes, systems, diseases, disasters, and public health issues. It includes reflections on how levels of governance, development and technical assistance affect countries' disaster readiness and health systems. In addressing inequalities between the rich and the poor, and unpacking how this affects public health services, policies, strategies and their collective implementation, the book aspires to improve standards of public health and quality of life for sustainable development globally. It provides a comprehensive overview of international health policies and aid structures, and pays particularly close attention to policies on HIV/AIDS in the workplace, discussing how HIV/AIDS has overshadowed non-communicable diseases (NCDs) such as hypertension and stroke, which are on the rise. This book will be of great benefit to students and researchers, as well as policymakers in governmental and non-governmental organisations, who have an interest in achieving greater sustainability and improved health for populations in low-, middle- and high-income countries. It will be an indispensable book for students in Public Health programmes, and related courses.

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.

The most common cause of premature death in the U.S. and in many of the world's countries is atherosclerotic cardiovascular disease, which includes coronary heart disease, peripheral vascular disease, and stroke. Most epidemiologic studies of risk factors for atherosclerosis have been conducted in adult populations, yet there is now clear evidence that the atherosclerotic process begins at a very early age. This book reviews recent findings that help physicians identify and manage children and adolescents who are at the highest risk for developing premature cardiovascular disease in later life. It reviews cholesterol levels, blood pressure levels, body size and tobacco use as risk factors for obesity, diabetes, coronary artery calcification and increased carotid artery intimal-medial thickness; it also discusses the measurement, familial aggregation, tracking and management of each of these risk factors.
The book merges epidemiology and pathophysiology with descriptions of risk factors in childhood and adolescence and how they affect blood vessels and the heart. The organization of the book makes clear the most up-to-date clinical recommendations from the National High Blood Pressure Education Program, the National Cholesterol Education Program, the American Academy of Pediatrics and the American Heart Association, while also presenting the results of epidemiologic studies that support the clinical recommendations. This provides the reader with both the science and application of pediatric preventive cardiology.
This book is for doctors and other health professionals who practice preventive cardiology in children, adolescents and young adults. It is for school nurses and schooladministrators who are committed to developing a healthful school environment with appropriate attention to school lunches and physical activity. For those who teach epidemiology and public health, it provides a complete discussion of pediatric atherosclerotic cardiovascular disease epidemiology. For medical historians, the book also offers an historical perspective on the development of knowledge regarding risk of cardiovascular disease in children, adolescents and young adults, and the clinical practice of pediatric prevention.

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.

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.

Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. "

Written for non-mathematically-oriented readers, this text features:

• "
• A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data
• An emphasis on how the terminology, interpretation, and estimation" "of familiar general linear models relates to those of more complex models for longitudinal data
• Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers understanding of the overall model-building process
• Sample results sections for each example to provide useful templates for published reports
• Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and M"plus" at www.PilesOfVariance.com to help readers apply the models to their own data

The book opens with the building blocks of longitudinal analysis general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces "unconditional "longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. "Conditional "longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data.

Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text."

'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

This title includes a number of Open Access chapters. The book provides a comprehensive perspective on the subject of obesity epidemiology, pathophysiology, and management of obesity. The chapters provide a better understanding of obesity and obesity-related diseases and offer an integrative framework for individualized dietary and exercise programs, behavior modification, pharmaceutical approaches, surgery, and population interventions to reduce the growing epidemic of obesity.

Appeals to a Wide Audience Fueled by more than 30 years of intensive research and debate on the impact of electromagnetic fields (EMF) on everyday life-starting with residential exposure to magnetic fields and the development of childhood cancer in the 70s and continuing with risk of exposure via wireless communications in present day-Epidemiology of Electromagnetic Fields addresses ongoing public and scientific controversy surrounding the possible effects of electromagnetic fields (EMF) to human health, and provides an in-depth introduction into the methodology of environmental epidemiology that is appropriate for all levels, from student to practicing engineer. Exposure to EMF Focusing primarily on EMF examples, the author presents the general principles and methodological concepts in environmental epidemiology. Topics of importance in the first part of the book include epidemiological study designs, exposure assessment methods and implications for the study results, as well as selection bias, confounding, and other biases including reverse causality and ecological fallacy. The second part of the book covers environmental epidemiological methods in detail and outlines key examples such as childhood leukemia and exposure to extremely low-frequency magnetic fields, as well as examples that look at brain tumors and mobile phone use. The book also offers a detailed discussion on the range of EMF sources and exposures. In addition, it highlights the sophisticated assessment methods required to address exposure situations, and provides a historical perspective. The third part of the book examines how EMF exposure from the use of wireless communication techniques and other challenges affect risk assessment today and also details future developments. Explores environmental epidemiological methods in detail, while critically discussing epidemiological findings Provides a state-of-the-art overview of the scientific evidence of the health effects of EMF Considers how novelty, the steep increase of radiofrequency (RF) EMF exposure from wireless communications, and other challenges affect risk assessment today Epidemiology of Electromagnetic Fields provides a thorough overview of the subject, and evaluates the scientific evidence surrounding the possible health effects of EMFs.

For young gay men who came of age in the United States in the 1980s, the HIV/AIDS epidemic was a formative experience in fear, hardship, and loss. Those who were diagnosed before 1996 suffered an exceptionally high rate of mortality, and the survivors - both the infected individuals and those close to them - today constitute a "bravest generation" in American history. The AIDS Generation: Stories of Survival and Resilience examines the strategies for survival and coping employed by these HIV-positive gay men, who together constitute the first generation of long-term survivors of the disease. Through interviews conducted by the author, it narrates the stories of gay men who have survived since the early days of the epidemic; documents and delineates the strategies and behaviors enacted by men of this generation to survive it; and examines the extent to which these approaches to survival inform and are informed by the broad body of literature on resilience and health. The stories and strategies detailed here, all used to combat the profound physical, emotional, and social challenges faced by those in the crosshairs of the AIDS epidemic, provide a gateway for understanding how individuals cope with chronic and life-threatening diseases. Halkitis takes readers on a journey of first-hand data collection (the interviews themselves), the popular culture representations of these phenomena, and his own experiences as one of the men of the AIDS generation. This riveting account will be of interest to health practitioners and historians throughout the clinical and social sciences - or to anyone with an interest in this important chapter in social history.

Advancing the development, validation, and use of patient-reported outcome (PRO) measures, Patient-Reported Outcomes: Measurement, Implementation and Interpretation helps readers develop and enrich their understanding of PRO methodology, particularly from a quantitative perspective. Designed for biopharmaceutical researchers and others in the health sciences community, it provides an up-to-date volume on conceptual and analytical issues of PRO measures. The book discusses key concepts relating to the measurement, implementation, and interpretation of PRO measures. It covers both introductory and advanced psychometric and biostatistical methods for constructing and analyzing PRO measures. The authors include many relevant real-life applications based on their extensive first-hand experiences in the pharmaceutical industry. They implement a wealth of simulated datasets to illustrate concepts and heighten understanding based on practical scenarios. For readers interested in conducting statistical analyses of PRO measures and delving more deeply into the analytic details, most chapters contain SAS code and output that illustrate the methodology. Along with providing numerous references, the book highlights current regulatory guidelines.

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbruck Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

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.

A complex disease involves many etiological and risk factors operating at multiple levels-molecular, cellular, organismal, and environmental. The incidence of such diseases as cancer, obesity, and diabetes are increasing in occurrence, urging us to think fundamentally and use a broader perspective to identify their connection and revolutionize treatments. The understanding of biological data derived from studying diseases can be enhanced by theories and mathematical models, which clarify the big picture and help to reveal the overarching mechanisms that govern complex biological phenomena. Focusing on diseases related to cellular energy metabolism, such as cancer and diabetes, Analysis of Complex Diseases: A Mathematical Perspective presents a holistic approach for illuminating the molecular mechanisms of these diseases and the evolutionary underpinning of their simultaneous epidemics. Using mathematics to identify patterns of deviation from normality, or the healthy state-spanning multiple levels from molecules to the organism-the author identifies a range of dynamical behaviors that correspond to either cellular physiology or pathology. He uses the information from multiple levels in order to develop a unified theory, which includes the discovery that certain diseases may stem from well-evolved, useful mechanisms activated in the wrong context. This book is divided into three parts. Part I focuses on the organismal level to describe normal physiology and how the body as a whole meets its functional requirements. Part II addresses the subcellular, molecular level to elucidate the organizing principles of cellular biomolecules to meet the demands of the organism. Part III examines complex diseases by combining information from the organismal level and the molecular level, offering a paradigm that can be extended to the study of other categories of diseases.

Statistical Analysis of Human Growth and Development is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. Designed for nonstatisticians and statisticians new to the analysis of growth and development data, the book collects methods scattered throughout the literature and explains how to use them to solve common research problems. It also discusses how well a method addresses a specific scientific question and how to interpret and present the analytic results. Stata is used to implement the analyses, with Stata codes and macros for generating example data sets, a detrended Q-Q plot, and weighted maximum likelihood estimation of binary items available on the book's CRC Press web page. After reviewing research designs and basic statistical tools, the author discusses the use of existing tools to transform raw data into analyzable variables and back-transform them to raw data. He covers regression analysis of quantitative, binary, and censored data as well as the analysis of repeated measurements and clustered data. He also describes the development of new growth references and developmental indices, the generation of key variables based on longitudinal data, and the processes to verify the validity and reliability of measurement tools. Looking at the larger picture of research practice, the book concludes with coverage of missing values, multiplicity problems, and multivariable regression. Along with two simulated data sets, numerous examples from real experimental and observational studies illustrate the concepts and methods. Although the book focuses on examples of anthropometric measurements and changes in cognitive, social-emotional, locomotor, and other abilities, the ideas are applicable to many other physical and psychosocial phenomena, such as lung function and depressive symptoms.

Because aging is accompanied by a steady decline in resistance to infectious diseases, the diagnosis and treatment of these diseases in the elderly is not only much more complex, but also often quite different from that for younger patients.

In the second edition of Infectious Disease in the Aging: A Clinical Handbook, a panel of well known and highly experienced geriatric physicians and infectious disease experts review the most important common infections affecting the elderly and delineate their well-proven diagnostic, therapeutic, and preventive techniques. Among the illnesses discussed are urinary tract infections, pneumonia, ocular infections, tuberculosis, and fungal and viral infections. In addition, there are detailed discussions of sepsis, infective endocarditis, intraabdominal infections, bacterial meningitis, osteomyelitis and septic arthritis, and prosthetic device infections.