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Items: 1 to 20 of 126

1.

An examination of data confidentiality and disclosure issues related to publication of empirical ROC curves.

Matthews GJ, Harel O.

Acad Radiol. 2013 Jul;20(7):889-96. doi: 10.1016/j.acra.2013.04.011.

2.
3.
4.

Measurement error and confidence intervals for ROC curves.

Tosteson TD, Buonaccorsi JP, Demidenko E, Wells WA.

Biom J. 2005 Aug;47(4):409-16.

PMID:
16161800
5.
6.

Direct estimation of the area under the receiver operating characteristic curve in the presence of verification bias.

He H, Lyness JM, McDermott MP.

Stat Med. 2009 Feb 1;28(3):361-76. doi: 10.1002/sim.3388.

7.

Bayesian bootstrap estimation of ROC curve.

Gu J, Ghosal S, Roy A.

Stat Med. 2008 Nov 20;27(26):5407-20. doi: 10.1002/sim.3366.

PMID:
18613217
8.

Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices.

Obuchowski NA, McClish DK.

Stat Med. 1997 Jul 15;16(13):1529-42.

PMID:
9249923
9.
10.

The partial area under the summary ROC curve.

Walter SD.

Stat Med. 2005 Jul 15;24(13):2025-40.

PMID:
15900606
11.

A permutation test for comparing ROC curves in multireader studies a multi-reader ROC, permutation test.

Bandos AI, Rockette HE, Gur D.

Acad Radiol. 2006 Apr;13(4):414-20.

PMID:
16554220
12.

An enhancement of ROC curves made them clinically relevant for diagnostic-test comparison and optimal-threshold determination.

Subtil F, Rabilloud M.

J Clin Epidemiol. 2015 Jul;68(7):752-9. doi: 10.1016/j.jclinepi.2015.01.003. Epub 2015 Jan 12.

PMID:
25660050
13.
14.

Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting.

Dendumrongsup T, Plumb AA, Halligan S, Fanshawe TR, Altman DG, Mallett S.

PLoS One. 2014 Dec 26;9(12):e116018. doi: 10.1371/journal.pone.0116018. eCollection 2014. Review.

15.

[Using ROC curves in clinical investigation: theoretical and practical issues].

Cerda J, Cifuentes L.

Rev Chilena Infectol. 2012 Apr;29(2):138-41. doi: 10.4067/S0716-10182012000200003. Spanish.

16.

A principled approach to setting optimal diagnostic thresholds: where ROC and indifference curves meet.

Irwin RJ, Irwin TC.

Eur J Intern Med. 2011 Jun;22(3):230-4. doi: 10.1016/j.ejim.2010.12.012. Epub 2011 Jan 26. Review.

PMID:
21570638
17.

Smooth non-parametric receiver operating characteristic (ROC) curves for continuous diagnostic tests.

Zou KH, Hall WJ, Shapiro DE.

Stat Med. 1997 Oct 15;16(19):2143-56.

PMID:
9330425
18.

Advances in statistical methodology for the evaluation of diagnostic and laboratory tests.

Campbell G.

Stat Med. 1994 Mar 15-Apr 15;13(5-7):499-508.

PMID:
8023031
19.

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

Du P, Tang L.

Stat Med. 2009 Jan 30;28(2):349-59. doi: 10.1002/sim.3465.

PMID:
18985706
20.

Semiparametric estimation of the relationship between ROC operating points and the test-result scale: application to the proper binormal model.

Pesce LL, Horsch K, Drukker K, Metz CE.

Acad Radiol. 2011 Dec;18(12):1537-48. doi: 10.1016/j.acra.2011.08.003.

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