The Authors: Professor Rory Wolfe, BSc, PhD, Professor of Biostatistics at the School of Public Health and Preventive Medicine, has broad research interests in biostatistics. Michael Abramson, MB, BS, PhD, FRACP is Professor of Clinical Epidemiology in the School of Public Health and Preventive Medicine, and a Specialist Physician in Allergy, Immunology and Respiratory Medicine at the Alfred Hospital in Melbourne. He has taught introductory biostatistics and uses statistical methods in his research.
INVITED REVIEW SERIES: MODERN STATISTICAL METHODS IN RESPIRATORY MEDICINE
Modern statistical methods in respiratory medicine
Article first published online: 23 DEC 2013
© 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology
Volume 19, Issue 1, pages 9–13, January 2014
How to Cite
Wolfe, R. and Abramson, M. J. (2014), Modern statistical methods in respiratory medicine. Respirology, 19: 9–13. doi: 10.1111/resp.12223
Series Editors: Rory Wolfe and Michael Abramson
- Issue published online: 23 DEC 2013
- Article first published online: 23 DEC 2013
- Manuscript Accepted: 24 OCT 2013
- Manuscript Received: 14 OCT 2013
Statistics sits right at the heart of scientific endeavour in respiratory medicine and many other disciplines. In this introductory article, some key epidemiological concepts such as representativeness, random sampling, association and causation, and confounding are reviewed. A brief introduction to basic statistics covering topics such as frequentist methods, confidence intervals, hypothesis testing, P values and Type II error is provided. Subsequent articles in this series will cover some modern statistical methods including regression models, analysis of repeated measures, causal diagrams, propensity scores, multiple imputation, accounting for measurement error, survival analysis, risk prediction, latent class analysis and meta-analysis.