[1] Baker, S. G., Pinsky, P. F., 2001. A proposed design
and analysis for comparing digital and analog
mammography: special receiver operating characteristic
methods for cancer screening. Journal of the American
Statistical Association 96, 421–428.
[2] Bamber, D., 1975. The area above the ordinal dominance
graph and the area below the receiver operating
characteristic graph. Journal of Mathematical
Psychology 12, 387–415.
[3] Bast Jr, R., 1993. Perspectives on the future of cancer
markers. Clinical Chemistry 39, 2444–2451.
[4] Beam, C. A., Conant, E. F., A.Sickles, E., Weinstein,S.
P., 2003. Evaluation of proscriptive health care policy
implementation in screening mammography. Radiology 229,
534–540.
[5] Blume, J. D., 2009. Bounding sample size projections
for the area under a roc curve. Journal of Statistical
Planning and Inference 139, 711–721.
[6] DeLong, E. R., DeLong, D. M., Clarke-Pearson, D. L.,
1988. Comparing the areas under two or more correlated
receiver operating characteristic curves: A
nonparametric approach. Biometrics 44, 837–845.
[7] Friedman, J. H., Popescu, B. E., 2004. Gradient
directed regularization for linear regression and
classification [online].
[8] Janes, H., Pepe, M., 2006. The optimal ratio of cases
to controls for estimating the classification accuracy
of a biomarker. Biostatistics 7, 456–468.
[9] Komori, O., Eguchi, S., 2010. A boosting method for
maximizing the partial area under the roc curve
[online]. BMC Bioinformatics 11, 314.
[10] Li, C., Liao, C., Liu, J., 2008. A non-inferiority
test for diagnostic accuracy based on the paired
partial areas under roc curves. Statistics in Medicine
27, 1762–1776.
[11] Liu, A., Schisterman, E., Zhu, Y., 2005. On linear
combinations of biomarkers to improve diagnostic
accuracy. Statistics in Medicine 24, 37–47.
[12] Ma, S., Huang, J., 2005. Regularized roc method for
disease classification and biomarker selection with
microarray data. Bioinformatics 21, 4356–4362.
[13] Marsaglia, G., 1972. Choosing a point from the surface
of a sphere. The Annals of Mathematical Statistics 43,
645–646.
[14] Marshall, R., 1989. The predictive value of simple
rules for combining two diagnostic tests. Biometrics
45, 1213–1222.
[15] McClish, D., 1989. Analyzing a portion of the ROC
curve. Medical Decision Making 9, 190–195.
[16] Muller, M., 1959. A note on a method for generating
points uniformly on n-dimensional spheres.
Communications of the ACM 2, 19–20.
[17] Obuchowski, N., McClish, D. K., 1997. Sample size
determination for diagnostic accuracy studies involving
binormal roc curve indices. Statistics in Medicine 16,
1529–1542.
[18] Obuchowski, N. A., 2000. Sample size tables for
receiver operating characteristic studies. American
Journal of Roentgenology 175, 603–608.
[19] Pepe, M., 2004. The Statistical Evaluation Of Medical
Tests For Classification And Prediction. Oxford
Statistical Science Series. Oxford University Press.
[20] Pepe, M., Thompson, M., 2000. Combining diagnostic
test results to increase accuracy. Biostatistics 1,123–140.
[21] Schott, J., 2005. Matrix Analysis For Statistics.
Wiley Series in Probability and Statistics. Wiley.
[22] Shao, J., 1999. Mathematical Statistics. Springer-
Verlag Inc.
[23] Silva, J. E., Mqrques, J. P., Jossinet, J., 2000.
Classification of breast tissue by electrical impedance
spectroscopy. Medical and Biological Engineering and
Computing 38, 26–30.
[24] Su, H. M., Voon, W. C., Lin, T. H., Lee, K. T., Chu,
C. S., Lee, M. Y., Sheu, S. H., Lai, W. T., 2004.
Ankle-brachial pressure index measured using an
automated oscillometric method as a predictor of the
severity of coronary atherosclerosis in patients with
coronary artery disease. The Kaohsiung Journal of
Medical Sciences 20, 268–272.
[25] Su, J., Liu, J., 1993. Linear combinations of multiple
diagnostic markers. Journal of the American Statistical
Association 88, 1350–1355.
[26] Thompson, M., Zucchini, W., 1989. On the statistical
analysis of ROC curves. Statistics in Medicine 8,
1277–1290.
[27] Tian, L., 2010. Confidence interval estimation of
partial area under curve based on combined biomarkers.
Computational Statistics &; Data Analysis 54, 466–472.
[28] Wang, Z., Chang, Y.-C. I., 2010. Marker selection via
maximizing the partial area under the roc curve of
linear risk scores. Biostatistics 12, 369–385.
[29] Woolas, R., Conaway, M., Xu, F., Jacobs, I., Yu, Y.,
Daly, L., Davies, A., O’Briant, K., Berchuck, A.,
Soper, J., et al., 1995. Combinations of multiple
serum markers are superior to individual assays for
discriminating malignant from benign pelvic masses.
Gynecologic Oncology 59, 111–116.