Praise for the Second Edition: "... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics "This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." - Journal of the Royal Statistical Society Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation. Features: Compares the relative merits and disadvantages of statistical methods for sample size calculations Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women's health Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.

Depressionen sind eines der Hauptprobleme in den Industriestaaten - wegen ihrer Verbreitung und volkswirtschaftlichen Konsequenzen. Neue Studien beweisen eine deutliche Unter- bzw. Fehlversorgung. Politik und Gesundheitswesen mussen Pravention, Gesundheitsforderung und die Versorgung Betroffener verbessern. Dies verlangt auch die Analyse des soziookonomischen und kulturellen Hintergrunds. Dieses Buch stellt hierfur das gegenwartige Wissen bereit. "

This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis. Statistics for Exercise Science and Health with Microsoft Office Excel: * Aids readers in analyzing their own data using the presented statistical techniques combined with Excel * Features comprehensive coverage of hypothesis testing and regression models to facilitate modeling in sports science * Utilizes Excel to enhance reader competency in data analysis and experimental designs * Includes coverage of both binomial and poison distributions with applications in exercise science and health * Provides solved examples and plentiful practice exercises throughout in addition to case studies to illustrate the discussed analytical techniques * Contains all needed definitions and formulas to aid readers in understanding different statistical concepts and developing the needed skills to solve research problems

Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

Injury is the leading cause of years of potential life lost in the United States, and one third of all fatal injuries are a result of intentional injuries or violence. Today, public health officials have identified violence as comparable in importance and impact to such previous epidemics as smallpox, tuberculosis, and syphilis. This volume offers a landmark assessment of the problem of violence from a public health perspective. Its aims is both to describe what is known about violence in our society, and to lead the way towards involving health professionals in both analysis and action. The authors, all internationally known experts in their fields, examine child, spouse, and elder abuse; sexual assault and rape; suicide; assaultive violence; and homicide. To each topic they bring an analysis of key issues in epidemiology, causal and risk factors, outcomes, and interventions. This timely work will be a valuable resource for public health professionals, criminologists, sociologists, social workers, educators, and all those concerned with violence in our communities.

This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis.

A comprehensive guidebook to the current methodologies and practices used in health surveys A unique and self-contained resource, Handbook of Health Survey Methods presents techniques necessary for confronting challenges that are specific to health survey research. The handbook guides readers through the development of sample designs, data collection procedures, and analytic methods for studies aimed at gathering health information on general and targeted populations. The book is organized into five well-defined sections: Design and Sampling Issues, Measurement Issues, Field Issues, Health Surveys of Special Populations, and Data Management and Analysis. Maintaining an easy-to-follow format, each chapter begins with an introduction, followed by an overview of the main concepts, theories, and applications associated with each topic. Finally, each chapter provides connections to relevant online resources for additional study and reference. The Handbook of Health Survey Methods features: *29 methodological chapters written by highly qualified experts in academia, research, and industry * A treatment of the best statistical practices and specific methodologies for collecting data from special populations such as sexual minorities, persons with disabilities, patients, and practitioners * Discussions on issues specific to health research including developing physical health and mental health measures, collecting information on sensitive topics, sampling for clinical trials, collecting biospecimens, working with proxy respondents, and linking health data to administrative and other external data sources * Numerous real-world examples from the latest research in the fields of public health, biomedicine, and health psychology Handbook of Health Survey Methods is an ideal reference for academics, researchers, and practitioners who apply survey methods and analyze data in the fields of biomedicine, public health, epidemiology, and biostatistics. The handbook is also a useful supplement for upper-undergraduate and graduate-level courses on survey methodology.

Genetic epidemiology plays a key role in discovering genetic factors influencing health and disease, and in understanding how genes and environmental risk factors interact. There is growing interest in this field within public health, with the goal of translating the results into promoting health and preventing disease in both families and populations. This textbook provides graduate students with a working knowledge of genetic epidemiology research methods. Following an overview of the field, the book reviews key genetic concepts, provides an update on relevant genomic technology, including genome-wide chips and DNA sequencing, and describes methods for assessing the magnitude of genetic influences on diseases and risk factors. The book focuses on research study designs for discovering disease susceptibility genes, including family-based linkage analysis, candidate gene and genome-side association studies, assessing gene-environment interactions and epistasis, studies of Non-Mendelian inheritance, and statistical analyses of data from these studies. Specific applications of each research method are illustrated using a variety of diseases and risk factors relevant to public health, and useful web-based genetic analysis software, human reference panels, and repositories, that can greatly facilitate this work, are described. Concluding with a review of ethical issues and a framework for translating human genomics research to clinical practice and public health benefit, this textbook is an essential new resource for graduate students in epidemiology and public health genetics.

A new edition of the comprehensive and practical introduction to managerial epidemiology and population health Managerial Epidemiology for Health Care Organizations has introduced the science of epidemiology and population health to students and practitioners in health management and health services for over sixteen years. The book covers epidemiology basics, introducing principles and traditional uses, and then expertly showing its contemporary uses in planning, evaluating, and managing health care for populations and the practical application in health care management. The book's practical and applied approach, with real-world examples sprinkled throughout, has made it the go-to book for managerial epidemiology and population health courses. Since the second edition was published in 2005, the health care landscape has undergone significant changes. Passage of the Patient Protection and Affordable Care Act and the incorporation of ICD-10 have impacted the entire health care system. This newly updated third edition will address these two significant changes, as well as several others that have taken place. It also features new chapters on reimbursement approaches and managing infection outbreaks, as well as updates to the four case study chapters that anchor the book. Witness how epidemiological principles are applied to the delivery of health care services and the management of health care organizations Examine the major changes brought on by the passage of health care reform and incorporation of ICD-10 Discover the core epidemiology principles and see how they are applied in planning, evaluating, and managing health care for populations If you're a student or professional in any area of health services, including health administration, nursing, and allied health, then Managerial Epidemiology for Health Care Organizations is the perfect book for you. It successfully demonstrates how health care executives can incorporate the practice of epidemiology into their various management functions and is rich with current examples, concepts, and case studies that reinforce the essential theories, methods, and applications of managerial epidemiology.

This highly successful guide, now in its firth edition with sales in excess of 26,000, is essential reading for all those requiring a basic understanding of epidemiology-the study of how often and why diseases occur in different groups of people.

Assuming no prior knowledge of the subject, it guides the novice through both the theory and practical pitfalls with the aid of familiar examples.

Subjects covered include:
What is Epidemiology?
Quantifiying Disease in Populations
Comparing Disease Rates
Measurement Error and Bias
Planning and Conducting a Survey
Ecological Studies
Longitudinal Studies
Case-control and Cross Sectional Studies
Experimental Studies
Screening
Outbreaks of Disease
Reading Epidemiolgical Reports

This concise and readable book, now revised and updated, is an invaluable tool for all health care professionals and medical students whether they are getting to grips with epidemiology for the first time or as a practical revision aid for those needing to refresh or update their knowledge.

Epidemiology, the so-called "science of public health," has undergone a boom in the last decade as public interest and engagement in population health has skyrocketed. While this boom has done much to spark advances in the technology of epidemiology, it has also made it harder for those who want to use epidemiology to guide policy and clinical practice to fully appreciate the meaning of the research findings. Interpreting Epidemiologic Evidence offers those who have had an introductory course in epidemiology the knowledge they need to make clear connections from research findings to practical applications. Written in clear and lively prose, it empowers students at all levels to evaluate a study's design, implementation, and ultimate findings, giving the guidance needed to apply the information appropriately. Liberal use of practical examples serves both to illustrate core concepts and to motivate readers to think critically about the causal connections that population health studies aim to explore. Completely revised and updated, this new edition of Interpreting Epidemiologic Evidence is an invaluable core text for both epidemiologists in training and practitioners across other disciplines with even an introductory knowledge of epidemiology.

With the accelerating discovery of human genes, public health professionals are increasingly confronted with a large body of scientific information that will guide public health action. Because the broad mission of public health is to fulfill society's interest in assuring conditions in which people can be healthy, the integration of new genetic information in public health research, policy and program development is unavoidable. Public health leadership is urgently needed to use genetic information to improve health and prevent disease, and to address ethical, legal and social issues resulting from inappropriate use of such information. In the not too-distant future, disease prevention and health promotion programs will routinely consider whether or not to use genetic information to help target behavioral, medical or environmental intervention activities in order to maximize benefit and minimize costs and harm to individuals. In anticipation of the expected growth at the interface of genetics and public health, this book delineates a framework for the integration of advances in human genetics into public health practice. It provides a comprehensive review of public health genetics, including chapters on important general issues such as newborn and other genetic screening, the delivery of genetic services, and the ethical, legal and social implications of the use of genetics within public health. It also reviews relevant clinical topics, the historical background, cross-cultural aspects, and communication issues. Contributors come from a wide range of fields including epidemiology, biostatistics, health policy and management, health services research, behavioral and social sciences, ethics, law, health economics, and laboratory sciences.

Written by a biostatistics expert with over 20 years of experience in the field, Bayesian Methods in Epidemiology presents statistical methods used in epidemiology from a Bayesian viewpoint. It employs the software package WinBUGS to carry out the analyses and offers the code in the text and for download online. The book examines study designs that investigate the association between exposure to risk factors and the occurrence of disease. It covers introductory adjustment techniques to compare mortality between states and regression methods to study the association between various risk factors and disease, including logistic regression, simple and multiple linear regression, categorical/ordinal regression, and nonlinear models. The text also introduces a Bayesian approach for the estimation of survival by life tables and illustrates other approaches to estimate survival, including a parametric model based on the Weibull distribution and the Cox proportional hazards (nonparametric) model. Using Bayesian methods to estimate the lead time of the modality, the author explains how to screen for a disease among individuals that do not exhibit any symptoms of the disease. With many examples and end-of-chapter exercises, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how these Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors.

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period, disease, etc. Although theory will be covered, the applied component will be equally as important with lots of practical examples offered. Features: Discusses the very latest developments on multivariate and multidimensional mapping. Gives a single state-of-the-art framework that unifies most of the previously proposed disease mapping approaches. Balances epidemiological and statistical points-of-view. Requires no previous knowledge of disease mapping. Includes practical sessions at the end of each chapter with WinBUGs/INLA and real world datasets. Supplies R code for the examples in the book so that they can be reproduced by the reader. About the Authors: Miguel A. Martinez Beneito has spent his whole career working as a statistician for public health services, first at the epidemiology unit of the Valencia (Spain) regional health administration and later as a researcher at the public health division of FISABIO, a regional bio-sanitary research center. He has been also the Bayesian Hierarchical Models professor for several seasons at the University of Valencia Biostatics Master. Paloma Botella Rocamora has spent most of her professional career in academia although she now works as a statistician for the epidemiology unit of the Valencia regional health administration. Most of her research has been devoted to developing and applying disease mapping models to real data, although her work as a statistician in an epidemiology unit makes her develop and apply statistical methods to health data, in general.

Praise for the First Edition

" . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."--Zentralblatt MATH

A new edition of the cutting-edge guide to diagnostic tests in medical research

In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations.

Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include:

Methods for tests designed to detect and locate lesions

Recommendations for covariate-adjustment

Methods for estimating and comparing predictive values and sample size calculations

Correcting techniques for verification and imperfect standard biases

Sample size calculation for multiple reader studies when pilot data are available

Updated meta-analysis methods, now incorporating random effects

Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS(R), and R software packages so that readers can conduct their own analyses.

Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.

Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology.

**THE SUNDAY TIMES BESTSELLER | BBC RADIO 4 BOOK OF THE WEEK** Preventable tells the extraordinary story of COVID-19 and how global politics shape our health - from a world-leading expert and the pandemic's go-to science communicator Professor Devi Sridhar has risen to prominence for her vital roles in communicating science to the public and speaking truth to power. In Preventable she highlights lessons learned from outbreaks past and present in a narrative that traces the COVID-19 pandemic - including her personal experience as a scientist - and sets out a vision for how we can better protect ourselves from the inevitable health crises to come. In gripping and heartfelt prose, Sridhar exposes the varied realities of those affected (from the jailed doctor in Wuhan who sounded the alarm, and the bored passengers marooned on the Diamond Princess cruise ship, to the daily nightmares of exhausted healthcare workers), and puts you in the room with key decision makers at crucial moments (from over-confident heads of states and their hesitant scientific advisors, to the beleaguered leaders of global health organisations). Sridhar vibrantly conveys the twists and turns of a plot that saw: deadlier variants emerge (contrary to the predictions of social media pundits who argued it would mutate to a milder form); the Pyrrhic victory in many countries of the false narrative of health versus the economy (those countries which controlled the virus, like Taiwan and Denmark, had a steadier recovery); countries with weak health systems like Senegal and Vietnam fare better than countries like the US and UK (which were consistently ranked as the most prepared); and the quickest development of game-changing vaccines in history (and their unfair distribution). Combining science, politics, ethics and economics, this definitive book dissects the global structures that determine our fate, and reveals the deep-seated economic and social inequalities at their heart - it will challenge, outrage and inspire. 'A brutally compelling reminder that if voices like Devi's had been listened to, so many more could have lived' OWEN JONES 'One of the most brilliant scientists in the world who has been proven consistently right in this crisis' PIERS MORGAN 'Excellent . . . Fair, clear and compelling' NICOLA STURGEON 'Those who have found Professor Devi Sridhar's expertise and calm advice invaluable since the arrival of Covid-19 will be glad to know that she has written Preventable' RACHEL COOKE, Guardian, Non-fiction to look out for in 2022

Disease Surveillance: Technological Contributions to Global Health Security reminds us of the continued vulnerability of the world to contagious infections. The book presents examples of disease surveillance systems and evaluates promising advances as well as opportunities for new systems. It also explains how newer technologies can allow countries to comply with the International Health Regulations established by the World Health Organization. The book covers various topics including international health regulations policy, challenges surrounding system deployment and implementation, data visualization techniques, the strengths and weaknesses of open source software, and legal considerations surrounding such software. This book will show you how new reporting requirements, combined with new technologies, big data sources, and sophisticated analytic approaches now enable the public health community to identify potential outbreaks and initiate a response earlier than at any other time in history.

Das Problem: Die kleine Stichprobe

In der Forschungspraxis der Psychologie, der Medizin und der Sozialwissenschaften hat es der Anwender statistischer Verfahren uberwiegend mit kleinen Stichproben zu tun. Der in der Statistik-Vorlesung gelernte t-Test oder die Varianzanalyse kann hier nicht eingesetzt werden.

Die Losung: Der kleine Bortz

Die Kurzgefasste Statistik fur die klinische Forschung setzt hier an: Es werden statistische Verfahren beschrieben, die bei kleinen Stichproben zur Hypothesenprufung angewandt werden konnen. Diese verteilungsfreien Verfahren setzen nur geringe Grundkenntnisse der Statistik voraus. Anwendungsbezogene Erklarungen zur Zielsetzung und Durchfuhrung von Untersuchungen sowie ausfuhrliche Zahlenbeispiele machen die Anwendung der Verfahren einfach nachvollziehbar."

Pocket Guide to Bacterial Infections provides information pertinent to the behaviour of bacterial cells during their interactions with different cell types of multiple host systems. This book will present the role of various bacterial pathogens affecting the host system. The book is to be organized flexibly so that chapters and topics are arranged with continuity from the former chapters. Each chapter has been made as self-contained as possible to promote this flexibility. This book will discuss each of the virulence properties of the bacteria with reference to their interacting hosts in a larger perspective. Kwey selling features: Summarizes the role various bacterial pahtogens affect the host system Reviews recent advances for combating different types of bacterial infections that infect different body parts Designed as an effective teaching and research tool providing up to date information on bacterial infections Defines important terms Written in a readable and direct writing style

Pocket Guide to Bacterial Infections provides information pertinent to the behaviour of bacterial cells during their interactions with different cell types of multiple host systems. This book will present the role of various bacterial pathogens affecting the host system. The book is to be organized flexibly so that chapters and topics are arranged with continuity from the former chapters. Each chapter has been made as self-contained as possible to promote this flexibility. This book will discuss each of the virulence properties of the bacteria with reference to their interacting hosts in a larger perspective. Kwey selling features: Summarizes the role various bacterial pahtogens affect the host system Reviews recent advances for combating different types of bacterial infections that infect different body parts Designed as an effective teaching and research tool providing up to date information on bacterial infections Defines important terms Written in a readable and direct writing style

"Methods and Applications of Statistics in Clinical Trials, Volume 2: Planning, Analysis, and Inferential Methods" includes updates of established literature from the Wiley Encyclopedia of Clinical Trials as well as original material based on the latest developments in clinical trials. Prepared by a leading expert, the second volume includes numerous contributions from current prominent experts in the field of medical research. In addition, the volume features:

- Multiple new articles exploring emerging topics, such as evaluation methods with threshold, empirical likelihood methods, nonparametric ROC analysis, over- and under-dispersed models, and multi-armed bandit problems

- Up-to-date research on the Cox proportional hazard model, frailty models, trial reports, intrarater reliability, conditional power, and the kappa index

- Key qualitative issues including cost-effectiveness analysis, publication bias, and regulatory issues, which are crucial to the planning and data management of clinical trials

This casebook is designed for use in courses on epidemiology or occupational epidemiology. The chapters are based on actual studies and are written by the principal investigators. They are divided into four parts: cohort studies, case-control and proportionate mortality studies, cross-sectional studies, and surveillance and screening studies. A brief introduction to each part describes the study design, and a statistical appendix is included so that students can easily find the tools needed to answer analytical questions in the text. Questions in each chapter deal with study design, data collection, analysis, and interpretation. Complete answers are provided at the end of each chapter. Data sets accompany many of the chapters, and most of the analytical questions can be answered with a pocket calculator.

The studies presented in this lucid, well-organized text involve a broad range of disease outcomes, including spontaneous abortion, carpal tunnel syndrome, kidney dysfunction, cytogenetic changes, ischemic heart disease, dermatitis, chronic renal disease, and several types of cancer. The exposures of interest are equally diverse, including VDT use, repetitive hand-wrist motion, heavy metals, carbon monoxide, diesel exhaust, lead, vinyl chloride, pesticides, solvents, silica, and acid mists. These outcomes and exposures cover many of the current topics of interest in occupational health.

Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many areas of the health sciences, including medicine, nursing, pharmacy, dentistry, and physical therapy, but are understandable to students in any field. The book can be used in a first-semester course in a health sciences program or in a service course for undergraduate students who plan to enter a health sciences program. The book begins by explaining the research context for statistics in the health sciences, which provides students with a framework for understanding why they need statistics as well as a foundation for the remainder of the text. It emphasizes kinds of variables and their relationships throughout, giving a substantive context for descriptive statistics, graphs, probability, inferential statistics, and interval estimation. The final chapter organizes the statistical procedures in a decision tree and leads students through a process of assessing research scenarios. Web ResourceThe authors have partnered with William Howard Beasley, who created the illustrations in the book, to offer all of the data sets, graphs, and graphing code in an online data repository via GitHub. A dedicated website gives information about the data sets and the authors' electronic flashcards for iOS and Android devices. These flashcards help students learn new terms and concepts.

A hands-on guide to using statistics in health research, from planning, through analysis, and on to reporting A Practical Approach to Using Statistics in Health Research offers an easy to use, step-by-step guide for using statistics in health research. The authors use their experience of statistics and health research to explain how statistics fit in to all stages of the research process. They explain how to determine necessary sample sizes, interpret whether there are statistically significant difference in outcomes between groups, and use measured effect sizes to decide whether any changes are large enough to be relevant to professional practice. The text walks you through how to identify the main outcome measure for your study and the factor which you think may influence that outcome and then determine what type of data will be used to record both of these. It then describes how this information is used to select the most appropriate methods to report and analyze your data. A step-by-step guide on how to use a range of common statistical procedures are then presented in separate chapters. To help you make sure that you are using statistics robustly, the authors also explore topics such as multiple testing and how to check whether measured data follows a normal distribution. Videos showing how to use computer packages to carry out all the various methods mentioned in the book are available on our companion web site. This book: - Covers statistical aspects of all the stages of health research from planning to final reporting - Explains how to report statistical planning, how analyses were performed, and the results and conclusion - Puts the spotlight on consideration of clinical significance and not just statistical significance - Explains the importance of reporting 95% confidence intervals for effect size - Includes a systematic guide for selection of statistical tests and uses example data sets and videos to help you understand exactly how to use statistics Written as an introductory guide to statistics for healthcare professionals, students and lecturers in the fields of pharmacy, nursing, medicine, dentistry, physiotherapy, and occupational therapy, A Practical Approach to Using Statistics in Health Research: From Planning to Reporting is a handy reference that focuses on the application of statistical methods within the health research context.