title: Interpretation of commonly used statistical regression models.
abstract: A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study.
authors.affiliation: Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Victorian Centre for Biostatistics (ViCBiostat), Melbourne, Victoria, Australia.
authors.forename: Jessica
authors.initials: J
authors.lastname: Kasza
authors.forename: Rory
authors.initials: R
authors.lastname: Wolfe
mesh_terms: D035843:Biomedical Research / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D015272:Pulmonary Medicine / Q000706:statistics & numerical data*; D012044:Regression Analysis
keywords: linear model; logistic model; ordinal logistic model; regression analysis.