Medical Statistics

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 5th edition of this popular introduction to statistics for the medical and health sciences has undergone a significant revision, with several new chapters added and examples refreshed throughout the book. Yet it retains its central philosophy to explain medical statistics with as little technical detail as possible, making it accessible to a wide audience.  Helpful multi-choice exercises are included at the end of each chapter, with answers provided at the end of the book. Each analysis technique is carefully explained and the mathematics kept to minimum. Written in a style suitable for statisticians and clinicians alike, this edition features many real and original examples, taken from the authors' combined many years' experience of designing and analysing clinical trials and teaching statistics. Students of the health sciences, such as medicine, nursing, dentistry, physiotherapy, occupational therapy, and radiography should find the book useful, with examples relevant to their disciplines. The aim of training courses in medical statistics pertinent to these areas is not to turn the students into medical statisticians but rather to help them interpret the published scientific literature and appreciate how to design studies and analyse data arising from their own projects. However, the reader who is about to design their own study and collect, analyse and report on their own data will benefit from a clearly written book on the subject which provides practical guidance to such issues. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, public health, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations.

Blackwell Publishing is delighted to announce that this book has been 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 presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics.» Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods. The second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data. Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact. Essential Medical Statistics is supported by a web site at www.blackwellpublishing.com/essentialmedstats. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.

This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to elementary statistics. The book presents a detailed account of the most important procedures for the analysis of data, from the calculation of simple proportions, to a variety of statistical tests, and the use of regression models for modeling of clinical outcomes. The level of mathematics is kept to a minimum to make the material easily accessible to the novice, and a multitude of illustrative cases are included in every chapter, drawn from the current research literature. The new edition has been completely revised and updated and includes new chapters on basic quantitative methods, measuring survival, measurement scales, diagnostic testing, bayesian methods, meta-analysis and systematic reviews. «… After years of trying and failing, this is the only book on statistics that i have managed to read and understand» – Naveed Kirmani, Surgical Registrar, South London Healthcare HHS Trust, UK

Medical Statistics at a Glance is a concise and accessible introduction and revision aid for this complex subject. The self-contained chapters explain the underlying concepts of medical statistics and provide a guide to the most commonly used statistical procedures. This new edition of Medical Statistics at a Glance: Presents key facts accompanied by clear and informative tables and diagrams Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of computer data analysis rather than complex hand calculations Includes extensive cross-referencing, a comprehensive glossary of terms and flow-charts to make it easier to choose appropriate tests Now provides the learning objectives for each chapter Includes a new chapter on Developing Prognostic Scores Includes new or expanded material on study management, multi-centre studies, sequential trials, bias and different methods to remove confounding in observational studies, multiple comparisons, ROC curves and checking assumptions in a logistic regression analysis The companion website at www.medstatsaag.com contains supplementary material including an extensive reference list and multiple choice questions (MCQs) with interactive answers for self-assessment. Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines. Reviews of the previous editions «The more familiar I have become with this book, the more I appreciate the clear presentation and unthreatening prose. It is now a valuable companion to my formal statistics course.» –International Journal of Epidemiology «I heartily recommend it, especially to first years, but it's equally appropriate for an intercalated BSc or Postgraduate research. If statistics give you headaches – buy it. If statistics are all you think about – buy it.» –GKT Gazette «…I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book.» –4th Year Medical Student, Barts and the London Chronicle, Spring 2003

Statistical methodology is of great importance to medical research and clinical practice. The Encyclopaedic Companion to Medical Statistics contains readable accounts of the key topics central to current research and practice. Each entry has been written by an individual chosen for both their expertise in the field and their ability to communicate statistical concepts successfully to medical researchers. Real examples from the biomedical literature and relevant illustrations feature in many entries and extensive cross–referencing signposts the reader to related entries. Key Features: Contains accounts of over 400 statistical topics central to current medical research. 80% of first edition entries updated and revised. Presents the latest techniques used at the cutting edge of medical research. Covers common errors in statistical analyses in medicine. Real examples from the biomedical literature and relevant illustrations feature throughout. Contains contributions from over 70 experts in the field. Medical researchers, researchers and practitioners in medical research and statistics will benefit greatly from this book.

Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics.  The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.

"…I know of no better book of its kind…" (Journal of the Royal Statistical Society, Vol 169 (1), January 2006) A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t–tests and chi–squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. Includes numerous worked examples and exercises within each chapter.

Explores mathematical statistics in its entirety—from the fundamentals to modern methods This book introduces readers to point estimation, confidence intervals, and statistical tests. Based on the general theory of linear models, it provides an in-depth overview of the following: analysis of variance (ANOVA) for models with fixed, random, and mixed effects; regression analysis is also first presented for linear models with fixed, random, and mixed effects before being expanded to nonlinear models; statistical multi-decision problems like statistical selection procedures (Bechhofer and Gupta) and sequential tests; and design of experiments from a mathematical-statistical point of view. Most analysis methods have been supplemented by formulae for minimal sample sizes. The chapters also contain exercises with hints for solutions. Translated from the successful German text, Mathematical Statistics requires knowledge of probability theory (combinatorics, probability distributions, functions and sequences of random variables), which is typically taught in the earlier semesters of scientific and mathematical study courses. It teaches readers all about statistical analysis and covers the design of experiments. The book also describes optimal allocation in the chapters on regression analysis. Additionally, it features a chapter devoted solely to experimental designs. Classroom-tested with exercises included Practice-oriented (taken from day-to-day statistical work of the authors) Includes further studies including design of experiments and sample sizing Presents and uses IBM SPSS Statistics 24 for practical calculations of data Mathematical Statistics is a recommended text for advanced students and practitioners of math, probability, and statistics.