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A good understanding of medical statistics is essential to evaluate medical research and to choose appropriate ways of implementing findings in clinical practice. The Oxford Handbook of Medical Statistics has been written to provide doctors and medical students with a comprehensive yet concise account of this often difficult subject.
Described by readers as a 'statistical Bible', this new edition maintains the accessibility and thoroughness of the original, and includes comprehensive updates including new sections on transitional medicine, cluster designs, and modern statistical packages. The Handbook promotes understanding and interpretation of statistical methods across a wide range of topics, from study design and sample size considerations, through t- and chi-squared tests, to complex multifactorial analyses, all using examples from published research. References and further reading are included, to allow deeper understanding on specific topics.
Featuring a new chapter on how to use this book in different medical contexts, the Oxford Handbook of Medical Statistics helps readers to conduct their own research and critically appraise others' work.
Oxford Handbook of Medical Statistics
by Peacock, Janet L.; Peacock, Phil J.Edition: 2nd
Format: Paperback
Pub. Date: 2020-08-11
Publisher(s): Oxford University Press
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Summary
Author Biography
Janet L. Peacock, Professor of Medical Statistics, King's College London, London, UK,Phil J. Peacock, Specialty Registrar in Paediatrics, Bristol Royal Hospital for Children, Bristol, UK
Janet first trained in Mathematics and Statistics and went on to specialise in medical statistics. She has worked in UK medical schools for over 25 years and now leads a team of 14 statisticians in the Division of Health and Social Care Research at King's. She collaborates in a many inter-disciplinary clinical studies, and conducts methodological research with statistical colleagues in UK and overseas.
Phil qualified in Medicine in 2007 and has since specialised in paediatrics, alongside training in research methods as an Academic Clinical Fellow. He has published several papers and enjoys helping others to understand and apply statistics in the context of medical research.
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