Variable selection for clinical prediction models in low-dimensional data - a simulation study comparing traditional regression and machine learning methods
- DOI
- 10.1186/s12874-026-02930-0
- Published
- 2026-07-07
- Container
- BMC Medical Research Methodology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12874-026-02930-0,
title = {Variable selection for clinical prediction models in low-dimensional data - a simulation study comparing traditional regression and machine learning methods},
author = {Johannes A. Vey and Georg Heinze and Meinhard Kieser},
year = {2026},
journal = {BMC Medical Research Methodology},
doi = {10.1186/s12874-026-02930-0},
url = {https://doi.org/10.1186/s12874-026-02930-0}
}RIS
TY - JOUR TI - Variable selection for clinical prediction models in low-dimensional data - a simulation study comparing traditional regression and machine learning methods AU - Johannes A. Vey AU - Georg Heinze AU - Meinhard Kieser PY - 2026 JO - BMC Medical Research Methodology DO - 10.1186/s12874-026-02930-0 UR - https://doi.org/10.1186/s12874-026-02930-0 ER -
APA
Vey, J. A., Heinze, G., & Kieser, M. (2026). Variable selection for clinical prediction models in low-dimensional data - a simulation study comparing traditional regression and machine learning methods. BMC Medical Research Methodology. https://doi.org/10.1186/s12874-026-02930-0
Source records
- crossref · retrieved 2026-09-26T03:58:14.125Z