Dealing with continuous variables and modelling non-linear associations in healthcare data: practical guide
Pedro Lopez-Ayala, Richard D Riley, Gary S. Collins, Tobias Zimmermann
Abstract
Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods are commonly used. This article highlights the importance of appropriately handling continuous variables, and illustrates the consequences of categorisation. This article also explains why assuming a linear relationship between the independent and dependent variable might be inappropriate, and describes how to use splines or fractional polynomials to model non-linear relationships.
Topics & Concepts
Computer scienceData scienceHealth careData miningEconomicsEconomic growthBlood Pressure and Hypertension StudiesHealth Systems, Economic Evaluations, Quality of LifeChronic Disease Management Strategies