The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
Abstract
In this paper we study a broad class of nonparametric statistics for comparing two diagnostic markers. One can compare the sensitivities of these diagnostic markers over restricted ranges of specificity by selecting an appropriate statistic from this class. As special cases, one can compare the entire area under the receiver-operator curve (Hanley & McNeil, 1982), or one can compare the sensitivities at a fixed common specificity. Usually we would recommend a comparison based on an average of sensitivities over a restricted high level of specificities. Test procedures and confidence intervals are based on asymptotic normality. These procedures are applicable for paired data, in which both diagnostic markers are performed on each subject, and for unpaired data. The procedures may be used to compare two real functions of multiple diagnostic markers as well as to compare individual markers.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Linear Statistical Inference and its Applications: Second Editon
Rao, C. R. (1973) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316436 · Cited by 10,489
Hanley, J. A., & McNeil, B. J. (1983) · Radiology · doi:10.1148/radiology.148.3.6878708 · Cited by 7,016
Empirical Processes with Applications to Statistics
Shorack, G. R., & Wellner, J. A. (2009) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9780898719017 · Cited by 2,310
A Radioimmunoassay Using a Monoclonal Antibody to Monitor the Course of Epithelial Ovarian Cancer
Bast, R. C., Klug, T. L., John, E. S., Jenison, E., Niloff, J. M., Lazarus, H., Berkowitz, R. S., Leavitt, T., Griffiths, C. T., Parker, L., et al. (1983) · New England Journal of Medicine · doi:10.1056/nejm198310133091503 · Cited by 2,135
Bamber, D. (1975) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(75)90001-2 · Cited by 1,439
(1982) · Cited by 1,288
Radioimmunometric assay for a monoclonal antibody-defined tumor marker, CA 19-9.
Del Villano, B. C., Brennan, S., Brock, P., Bucher, C., Liu, V, McClure, M., Rake, B., Space, S., Westrick, B., Schoemaker, H., et al. (1983) · Clinical Chemistry · doi:10.1093/clinchem/29.3.549 · Cited by 506
On Some Convergence Properties of UStatistics
Sen, P. K. (1960) · Calcutta Statistical Association Bulletin · doi:10.1177/0008068319600101 · Cited by 184
Cited by
(2013) · Europe PMC (PubMed Central) · Cited by 2,089
Phases of Biomarker Development for Early Detection of Cancer
Pepe, M. S., Etzioni, R., Feng, Z., Potter, J. D., Thompson, M. L., Thornquist, M., Winget, M., & Yasui, Y. (2001) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/93.14.1054 · Cited by 1,686
Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models
Zou, K. H., O’Malley, A. J., & Mauri, L. (2007) · Circulation · doi:10.1161/circulationaha.105.594929 · Cited by 1,473
Pepe, M. S. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh101 · Cited by 1,276
Projecting Individualized Absolute Invasive Breast Cancer Risk in African American Women
Gail, M. H., Costantino, J. P., Pee, D., Bondy, M., Newman, L., Selvan, M., Anderson, G. L., Malone, K. E., Marchbanks, P. A., McCaskill-Stevens, W., et al. (2007) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djm223 · Cited by 356
Self-citation
Metadata
- Authors
- WIEAND, S., GAIL, M. H., JAMES, B. R., & JAMES, K. L.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1989
- Volume
- 76
- Issue
- 3
- Pages
- 585-592
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2119029887
- Cited by
- 355
- References
- 14
- FWCI
- 3.68
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data. https://app.cochat.ai/papers/10.1093/biomet/76.3.585
- The paper
- WIEAND, S., GAIL, M. H., JAMES, B. R., & JAMES, K. L. (1989). A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data. Biometrika. https://doi.org/10.1093/biomet/76.3.585
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
