Explains the purpose of statistical methods in medical studies & analyzes the statistical techniques used by clinical investigators, with special emphasis on studies published in The New England Journal of Medicine. Clarifies fundamental concepts of statistical design & analysis & facilitates the understanding of research results.

Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a 'must-have' textbook for anyone who needs a clear logical guide to the subject. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the statistical principles used in the medical literature. Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.

Holistic approach to understanding medical statistics This hands-on guide is much more than a basic medical statistics introduction. It equips you with the statistical tools required for evidence-based clinical research. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. Showing you how to: analyse data with the help of data set examples (Click here to download datasets) select the correct statistics and report results for publication or presentation understand and critically appraise results reported in the literature Each statistical test is linked to the research question and the type of study design used. There are also checklists for critically appraising the literature and web links to useful internet sites. Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. Critical appraisal guidelines at the end of each chapter help the reader evaluate the statistical data in their particular contexts.

The majority of medical research involves quantitative methods and so it is essential to be able to understand and interpret statistics. This book shows readers how to develop the skills required to critically appraise research evidence effectively, and how to conduct research and communicate their findings.

In 1969 the first edition of this book introduced the concepts of statistics and their medical application to readers with no formal training in this area. While retaining this basic aim, the authors have expanded the coverage in each subsequent edition to keep pace with the increasing use and sophistication of statistics in medical research. This fifth edition has undergone major restructuring, with some sections completely rewritten; it is now more logically organized and more user friendly (with the addition of 'summary boxes' throughout the text). It incorporates new statistical techniques and approaches that have made an appearance since the last edition. In addition, some chapters or chapter headings are specifically marked to signify material that is more difficult than the material in which it is embedded - such sections or chapters can be omitted at first reading. Several new chapters have been added . "Associations: Chance, Confounded and Causal?" explains without any formulae the concepts underlying confounding, confidence intervals and p values, and the interpretation of associations observed in research investigations. Another new chapter considers sample size calculations in some detail and provides, in addition to the relevant formulae, useful tables that should give the researcher an indication of the order of magnitude of the number of subjects he or she might require in different situations.

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. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch.The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field.Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research.