Stephen J. Walters – författare

An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials. Quality of Life (QoL) outcomes or Person/Patient Reported Outcome Measures (PROMs) are now frequently being used in randomised controlled trials (RCTs) and observational studies. This book provides a practical guide to the design, analysis and interpretation of studies that use such outcomes.QoL outcomes tend to generate data with discrete, bounded and skewed distributions. Many investigators are concerned about the appropriateness of using standard statistical methods to analyse QoL data and want guidance on what methods to use. QoL outcomes are frequently used in cross-sectional surveys and non-randomised health-care evaluations. Provides a user-friendly guide to the design and analysis of clinical trials and observational studies in relation to QoL outcomes.Discusses the problems caused by QoL outcomes and presents intervention options to help tackle them.Guides the reader step-by-step through the selection of appropriate QoLs. Features exercises and solutions and a supporting website providing downloadable data files.Illustrated throughout with examples and case studies drawn from the author’s experience, this book offers statisticians and clinicians guidance on choosing between the numerous available QoL instruments.

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.

A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials.  The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible styleFeatures real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trialsDemonstrates the use of R, Stata and SPSS for statistical analysisIncludes computer code so the reader can replicate all the analysesDiscusses neglected areas such as ethics and practical issues in running cluster randomised trialsHow to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.