Oxford Handbook of Medical Statistics

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.

About the Authors

Janet L. Peacock, Professor of Epidemiology and Biomedical Data Science, Dartmouth College US, and Phil J. Peacock, Specialty Registrar in Paediatric Emergency Medicine, Oxford University Hospitals, UK UK

Janet is a biostatistician who has worked in UK and US Medical Schools for many years collaborating in research studies, particularly in paediatrics. She is also Emeritus Professor of Medical Statistics at King's College, London. Her main focus continues to be the use and extension of statistical methods in epidemiological studies. She is passionate about communicating statistics clearly and making results clinically meaningful without losing statistical rigour.

Phil is in the final months of subspecialty training in paediatric emergency medicine in Oxford, having previously undertaken core paediatric training in Bristol. He has published several research papers, and enjoys helping clinicians to better understand statistics, engage with clinical research, and practice evidence-based medicine.