It is not necessary to know how to do a statistical analysis to critically appraise a paper. However, it is necessary to have a grasp of the basics, of whether the right test has been used and how to interpret the resulting figures. Short, readable, and useful, this book provides the essential, basic information without becoming bogged down in the

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.

This long awaited second edition of this bestseller continues toprovide a comprehensive, user friendly, down-to-earth guide toelementary statistics. The book presents a detailed account ofthe most important procedures for the analysis of data, from thecalculation of simple proportions, to a variety of statisticaltests, and the use of regression models for modeling of clinicaloutcomes. The level of mathematics is kept to a minimum to make thematerial easily accessible to the novice, and a multitude ofillustrative cases are included in every chapter, drawn from thecurrent research literature. The new edition has beencompletely revised and updated and includes new chapters on basicquantitative methods, measuring survival, measurement scales,diagnostic testing, bayesian methods, meta-analysis and systematicreviews. "... After years of trying and failing, this is the only book onstatistics that i have managed to read and understand" - NaveedKirmani, Surgical Registrar, South London Healthcare HHS Trust,UK

Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises Two-part design features course material and a professional reference section Chapter summaries provide a review of formulas, method algorithms, and check lists Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions Updated database coverage and additional exercises Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression Thorough discussion on required sample size

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.

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.

Blackwell Publishing is delighted to announce that this book hasbeen Highly Commended in the 2004 BMA Medical Book Competition.Here is the judges' summary of this book: "This is a technical book on a technical subject but presentedin a delightful way. There are many books on statistics for doctorsbut there are few that are excellent and this is certainly one ofthem. Statistics is not an easy subject to teach or write about.The authors have succeeded in producing a book that is as good asit can get. For the keen student who does not want a book formathematicians, this is an excellent first book on medicalstatistics." Essential Medical Statistics is a classic amongst medicalstatisticians. An introductory textbook, it presents statisticswith a clarity and logic that demystifies the subject, whileproviding a comprehensive coverage of advanced as well as basicmethods. The second edition of Essential Medical Statistics hasbeen comprehensively revised and updated to include modernstatistical methods and modern approaches to statistical analysis,while retaining the approachable and non-mathematical style of thefirst edition. The book now includes full coverage of the mostcommonly used regression models, multiple linear regression,logistic regression, Poisson regression and Cox regression, as wellas a chapter on general issues in regression modelling. Inaddition, new chapters introduce more advanced topics such asmeta-analysis, likelihood, bootstrapping and robust standarderrors, and analysis of clustered data. Aimed at students of medical statistics, medical researchers,public health practitioners and practising clinicians usingstatistics in their daily work, the book is designed as both ateaching and a reference text. The format of the book is clear withhighlighted formulae and worked examples, so that all concepts arepresented in a simple, practical and easy-to-understand way. Thesecond edition enhances the emphasis on choice of appropriatemethods with new chapters on strategies for analysis and measuresof association and impact. Essential Medical Statistics is supported by a web siteat www.blackwellpublishing.com/essentialmedstats. Thisuseful online resource provides statistical datasets to download,as well as sample chapters and future updates.

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.

This volume presents a comprehensive and comprehensible set of guidelines for reporting the statistical analyses and research designs and activities commonly used in biomedical research.