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Cited by 278

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Linear Combinations of Multiple Diagnostic Markers

Su, John Q., Liu, Jun S.·1993·Journal of the American Statistical Association

Abstract

The receiver operating characteristic (ROC) curve is a simple and meaningful measure to assess the usefulness of diagnostic markers. To use the information carried by multiple markers, we note that Fisher's linear discriminant function provides a linear combination of markers to maximize the sensitivity over the entire specificity range uniformly under the multivariate normal distribution model with proportional covariance matrices. With no restriction on covariance matrices, we also provide a solution of the best linear combination of markers in the sense that the area under the ROC curve of this combination is maximized among all possible linear combinations. We illustrate both situations discussed in the article with a cancer clinical trial data.

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Metadata

Authors
Su, J. Q., & Liu, J. S.
Venue
Journal of the American Statistical Association
Published
1993-12
Volume
88
Issue
424
Pages
1350-1355
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W2048390639
Cited by
278
References
19
FWCI
0.00
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Linear Combinations of Multiple Diagnostic Markers. https://app.cochat.ai/papers/10.1080/01621459.1993.10476417
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Su, J. Q., & Liu, J. S. (1993). Linear Combinations of Multiple Diagnostic Markers. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1993.10476417

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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.