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How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research: Statistics in Practice

Autor M. Campbell
en Limba Engleză Hardback – 15 mai 2014
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 style * Features real examples taken from the authors' extensive practitioner experience of designing and analysing clinical trials * Demonstrates the use of R, Stata and SPSS for statistical analysis * Includes computer code so the reader can replicate all the analyses * Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How 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.
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Specificații

ISBN-13: 9781119992028
ISBN-10: 1119992028
Pagini: 264
Ilustrații: illustrations
Dimensiuni: 170 x 244 x 16 mm
Greutate: 0.57 kg
Editura: Wiley
Seria Statistics in Practice

Locul publicării:Chichester, United Kingdom

Public țintă

Applied statisticians and quantitative researchers working in the biopharmaceutical industry, academia/higher education, medical and public health organisations.  Post graduate working in biomedical statistics; public health/epidemiology, medical and health sciences students