The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Youden Index and the optimal threshold for markers with mass at zero
Open accessAbstract
The Youden Index is often used as a summary measure of the receiver operating characteristic curve. It measures the effectiveness of a diagnostic marker and permits the selection of an optimal threshold value or cutoff point for the biomarker of interest. Some markers, while basically continuous and positive, have a spike or positive mass of probability at the value zero. We provide a flexible modeling approach for estimating the Youden Index and its associated cutoff point for such spiked data and compare it with the standard empirical approach. We show how this modeling approach can be adjusted to take covariate information into account. This approach is applied to data on the Coronary Calcium Score, a marker for atherosclerosis. Published in 2007 by John Wiley & Sons, Ltd.
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Citations
Cites
Comparing the Areas Under Two Correlated ROC Curves: Parametric and Non‐Parametric Approaches
Molodianovitch, K., Faraggi, D., & Reiser, B. (2006) · Biometrical Journal · doi:10.1002/bimj.200610223 · Cited by 131
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Cited by
Classification accuracy and cut point selection
Liu, X. (2012) · Statistics in Medicine · doi:10.1002/sim.4509 · Cited by 676
The Performance of Risk Prediction Models
Gerds, T. A., Cai, T., & Schumacher, M. (2008) · Biometrical Journal · doi:10.1002/bimj.200810443 · Cited by 288
Metadata
- Authors
- Schisterman, E. F., Faraggi, D., Reiser, B., & Hu, J.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2007-07-11
- Volume
- 27
- Issue
- 2
- Pages
- 297-315
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2098860390
- Cited by
- 207
- References
- 1
- FWCI
- 2.10
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
