Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research. Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

Book is unique in being written for people who want to be able to make sense of published studies, or embark on their own studies, without getting bogged down by the details of how to use specific methods.

Providing everything the researcher, in a health care setting, needs to know about undertaking and completing a research project, this book provides detailed information about the various types of research projects that might be undertaken.

The second volume in the Wiley reference series in Biostatistics. Featuring articles from the prestigious Encyclopedia of Biostatistics, many of which have been fully revised and updated to include recent developments, Biostatistics in Clinical Trials also includes up to 25% newly commissioned material reflecting the latest thinking in: Bayesian methods Benefit/risk assessment Cost-effectiveness Ethics Fraud With exceptional contributions from leading experts in academia, government and industry, Biostatistics in Clinical Trials has been designed to complement existing texts by providing extensive, up-to-date coverage and introducing the reader to the research literature. Offering comprehensive coverage of all aspects of clinical trials Biostatistics in Clinical Trials: Includes concise definitions and introductions to numerous concepts found in current literature Discusses the software and textbooks available Uses extensive cross-references helping to facilitate further research and enabling the reader to locate definitions and related concepts Biostatistics in Clinical Trials offers both academics and practitioners from various disciplines and settings, such as universities, the pharmaceutical industry and clinical research organisations, up-to-date information as well as references to assist professionals involved in the design and conduct of clinical trials.

This book outlines the essential knowledge required for the management of critically ill and severely injured children. It is designed to facilitate successful completion of the Pediatric Emergency Medicine Board Examination of the American Board of Pediatrics (ABP). Each chapter follows a Question & Answer format, covering major areas in pediatrics such as cardiology, dermatology, nephrology, surgery and trauma. The book concludes with a comprehensive practice test, allowing it to function as a well-rounded reference and study guide. Prepare for the Pediatric Emergency Medicine Board Examination is an essential resource for any clinician or trainee seeking a concise review of how to manage critically ill and severely injured children.

From 'Abcissa' to 'Zygosity determination' - this accessible introduction to the terminology of medical statistics describes more than 1500 terms all clearly explained, illustrated and defined in non-technical language, without any mathematical formulae! With the majority of terms revised and updated and the addition of more than 100 brand new definitions, this new edition will enable medical students to quickly grasp the meaning of any of the statistical terms they encounter when reading the medical literature. Furthermore, annotated comments are used judiciously to warn the unwary of some of the common pitfalls that accompany some cherished biomedical statistical techniques. Wherever possible, the definitions are supplemented with a reference to further reading where the reader may gain a deeper insight, so whilst the definitions are easily disgestible, they also provide a stepping stone to a more sophisticated comprehension. Statistical terminology can be quite bewildering for clinicians: this guide will be a lifesaver.

Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting mathematical details and complicated formulae, the text provides SAS program

Hugely popular textbook on survival analysis for graduate students of statistics and biostatistics, mainly due to its accessibility and breadth of examples. This is a standard course on graduate programs in biostatistics and statistics, and this is one of the most popular textbooks. Updated with modern methods covering Bayesian survival analysis, joint models, and more.

Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.

Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.