A semiparametric hypothesis testing procedure for the ROC curve area under a density ratio model

Computational Statistics and Data Analysis

Volumn 50, Issue 7, 2006, Pages 1855-1876

  Zhang, Biao ^a  

^a UNIVERSITY OF TOLEDO   (United States)

Author keywords

Binormal model; Chi squared; Density ratio model; Gaussian process; Local alternative; Logistic regression model; Maximum likelihood; Power; ROC curve; Wald test

Indexed keywords

ASYMPTOTIC STABILITY; COMPUTATIONAL METHODS; COMPUTER SIMULATION; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; REGRESSION ANALYSIS;

BINORMAL MODELS; CHI-SQUARED; DENSITY RATIO MODELS; GAUSSIAN PROCESS; LOCAL ALTERNATIVE; LOGISTIC REGRESSION MODELS; MAXIMUM LIKELIHOOD; POWER; ROC CURVE; WALD TEST;

STATISTICAL TESTS;

EID: 30144433379     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2005.02.001     Document Type: Article

References (31)

1. C.B. Begg Advances in statistical methodology for diagnostic medicine in the 1980's Statist. Med. 10 1991 1887 1895
2. P. Billingsley Convergence of Probability Measures 1968 Wiley New York
3. D.D. Dorfman, K.S. Berbaum, and C.E. Metz Receiver operating characteristic rating analysis: generalization to the population of readers and cases with the jack-knife method Invest. Radiol. 27 1992 723 731
4. B. Efron, and R. Tibshirani An Introduction to the Bootstrap 1993 Chapman & Hall New York
5. M.J. Goddard, and I. Hinberg Receiver operating characteristic (ROC) curves and non-normal data: an empirical study Statist. Med. 9 1990 325 337
6. F. Hsieh, and B.W. Turnbull Nonparametric estimation of the receiver operating characteristic curve Ann. Statist. 24 1996 25 40
7. Y. Jiang, C.E. Metz, and R.M. Nishikawa A receiver operating characteristic partial area index for highly sensitive diagnostic tests Radiology 201 1996 745 750
8. R. Kay, and S. Little Transformations of the explanatory variables in the logistic regression model for binary data Biometrika 74 1987 495 501
9. E.L. Lehmann Elements of Large-Sample Theory 1999 Springer New York
10. G. Li, R.C. Tiwari, and M.T. Wells Semiparametric inference for a quantile comparison function with applications to receiver operating characteristic curves Biometrika 86 1999 487 502
11. C.J. Lloyd Using smoothed receiver operating characteristic curves to summarize and compare diagnostic systems J. Am. Statist. Assoc. 93 1998 1356 1364
12. C.J. Lloyd Semi-parametric estimation of ROC curves based on binomial regression modelling Aust. New Zeal. J. Statist. 44 2002 193 204
13. C.J. Lloyd Estimation of a convex ROC curve Statist. Prob. Lett. 59 2002 99 111
14. D.K. McClish Determining a range of false-positive rates for which ROC curves differ Med. Decis. Making 10 1990 283 287
15. C.E. Metz Statistical analysis of ROC data in evaluating diagnostic performance D. Herbert R. Myers Multiple Regression Analysis Applications in the Health Sciences 1986 American Institute of Physics New York 365 384
16. C.E. Metz, and H.B. Kronman Statistical significance tests for binormal ROC curves J. Math. Psychol. 22 1980 218 243
17. C.E. Metz, P. Wang, and H.B. Kronman A new approach for testing the significance of differences between ROC curves measured from correlated data F. Deconinck Information Processing in Medical Imaging 1984 Nijhoff The Hague, The Netherlands 432 445
18. C.E. Metz, B.A. Herman, and C.A. Roe Statistical comparison of two ROC curve estimates obtained from partially-paired datasets Med. Decis. Making 18 1998 110 121
19. C.E. Metz, B.A. Herman, and J.H. Shen Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously distributed data Statist. Med. 17 1998 1033 1053
20. M.S. Pepe Receiver operating characteristic methodology J. Am. Statist. Assoc. 95 2000 308 311
21. M.S. Pepe An interpretation for ROC curve and inference using GLM procedures Biometrics 56 2000 352 359
22. M.S. Pepe The Statistical Evaluation of Medical Tests for Classification and Prediction 2003 Oxford University Press New York
23. J. Qin, and B. Zhang A goodness-of-fit test for logistic regression models based on case-control data Biometrika 84 1997 609 618
24. J. Qin, and B. Zhang Using logistic regression procedures for estimating receiver operating characteristic curves Biometrika 90 2003 585 596
25. A.Y. Toledano, and C. Gatsonis Ordinal regression methodology for ROC curves derived from correlated data Statist. Med. 15 1996 1807 1826
26. E.S. Venkatraman, and C.B. Begg A distribution free procedure for comparing receiver operating characteristic curves from a paired experiment Biometrika 83 1996 835 848
27. S. Wieand, M.H. Gail, B.R. James, and K.L. James A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data Biometrika 76 1989 585 592
28. B. Zhang Quantile estimation under a two-sample semi-parametric model Bernoulli 6 2000 491 511
29. X.H. Zhou, and C.A. Gatsonis A simple method for comparing correlated ROC curves using incomplete data Statist. Med. 15 1996 1687 1693
30. X.H. Zhou, D.K. McClish, and N.A. Obuchowski Statistical Methods in Diagnostic Medicine 2002 Wiley New York
31. K.H. Zou, and W.J. Hall Two transformation models for estimating an ROC curve derived from continuous data J. Appl. Statist. 27 2000 621 631