Evaluating AUC estimators across complex sampling designs: insights from COVID-19 patient data
The use of the design-based AUC estimator is recommended over the traditional one when working with complex survey data in order to avoid biased AUC estimates.
Authors
- Amaia Iparragirre (ORCID: https://orcid.org/0000-0002-0660-6535)
- Irantzu Barrio (ORCID: https://orcid.org/0000-0003-0648-5769)
- José María Quintana (ORCID: https://orcid.org/0000-0003-2170-7876)
Institutions
- University of the Basque Country (ES)
- Basque Center for Applied Mathematics (ES)
- Red de Investigación en Actividades Preventivas y Promoción de la Salud (ES)
- Hospital de Galdakao (ES)
- Bioef - Fundación Vasca de Innovación e Investigación Sanitarias (ES)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2025-08-08
- DOI
- https://doi.org/10.1186/s12874-025-02615-0
- Primary Topic
- Statistical Methods and Bayesian Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Hezkuntza, Hizkuntza Politika Eta Kultura Saila, Eusko Jaurlaritza
- Eusko Jaurlaritza
- Euskal Herriko Unibertsitatea
- Ministerio de Ciencia e Innovación
- Basque Center for Applied Mathematics
- Agencia Estatal de Investigación