Dealing with continuous variables and modelling non-linear associations in healthcare data: practical guide
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.
Authors
- Richard D Riley (ORCID: https://orcid.org/0000-0001-8699-0735)
- Professor Gary S. Collins (ORCID: https://orcid.org/0000-0002-2772-2316)
- Tobias Zimmermann (ORCID: https://orcid.org/0000-0002-6862-5205)
- Pedro Lopez-Ayala
Institutions
- University of Basel (CH)
- Nuffield Orthopaedic Centre (GB)
- University Hospital of Basel (CH)
- Bury College (GB)
- University College Birmingham (GB)
- University of Oxford (GB)
- NIHR Birmingham Biomedical Research Centre (GB)
- University College London (GB)
- University of Birmingham (GB)
Publication Details
- Journal
- BMJ
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1136/bmj-2024-082440
- Citations
- 29
- Primary Topic
- Blood Pressure and Hypertension Studies
- Type
- article
- Field-Weighted Citation Impact
- 40.26
Funders
- University Hospitals Birmingham NHS Foundation Trust
- Cancer Research UK
- National Institute for Health and Care Research
- Department of Health and Social Care
- Imperial College London
- University College London
- Engineering and Physical Sciences Research Council
- Birmingham Biomedical Research Centre