商品簡介
This comprehensive workbook contains a variety of self-assessment methods that allow readers to test their statistical knowledge, put it into practice, and apply it in a medical context, while also providing guidance when critically appraising published literature. It is designed to support the best-selling third edition of Medical Statistics at a Glance, to which it is fully cross-referenced, but may be used independently of it.
Ideal for medical students, junior doctors, researchers and anyone working in the biomedical and pharmaceutical disciplines who wants to feel more confident in basic medical statistics, the title includes:
‧ Over 80 MCQs, each testing knowledge of a single statistical concept or aspect of study interpretation
‧ 29 structured questions to explore in greater depth several statistical techniques or principles, including the choice of appropriate statistical analyses and the interpretation of study findings
‧ Templates for the appraisal of clinical trials and observational studies, plus full appraisals of two published papers to demonstrate the use of these templates in practice
‧ Detailed step-by-step analyses of two substantial data sets (also available at www.medstatsaag.com) to demonstrate the application of statistical procedures to real-life research
Medical Statistics at a Glance Workbook is the ideal resource to test statistical knowledge and improve analytical and interpretational skills.
Additional resources are available at www.medstatsaag.com, including:
‧ Excel datasets to accompany the data analysis section
‧ Downloadable PDFs of two templates for critical appraisal
‧ Links to online further reading
‧ Supplementary MCQs
作者簡介
Aviva Petrie is Head of Biostatistics Unit and Senior Lecturer, Eastman Dental Institute, University College London; Honorary Lecturer in Medical Statistics, Medical Statistics Unit, London School of Hygiene and Tropical Medicine
Caroline Sabin is Professor of Medical Statistics and Epidemiology, Research Department of Infection and Population Health, Division of Population Health, University College London, Royal Free Campus
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