title: Modern statistical methods in respiratory medicine.
abstract: 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.
authors.affiliation: School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
authors.forename: Rory
authors.initials: R
authors.lastname: Wolfe
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Abramson
mesh_terms: D056808:Biostatistics / Q000379:methods*; D006801:Humans; D015272:Pulmonary Medicine / Q000706:statistics & numerical data*; D012107:Research Design; D012140:Respiratory Tract Diseases
keywords: association; causality; estimation; sampling; statistics