Lehmann family of ROC curves

Medical Decision Making

Volumn 30, Issue 4, 2010, Pages 509-517

  Gönen, Mithat ^a   Heller, Glenn ^a  

^a MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

Author keywords

accuracy; clustered data; concordance; proportional hazards; regression

Indexed keywords

ARTICLE; CLUSTER ANALYSIS; HUMAN; RECEIVER OPERATING CHARACTERISTIC; THEORETICAL MODEL;

CLUSTER ANALYSIS; HUMANS; MODELS, THEORETICAL; ROC CURVE;

EID: 77954907398     PISSN: 0272989X     EISSN: 1552681X     Source Type: Journal    
DOI: 10.1177/0272989X09360067     Document Type: Article

References (26)

1. Pratt JW, Gibbons JD Concepts of Nonparametric Theory. New York: Springer Verlag ; 1981.
2. Dorfman DD, Alf E. Maximum likelihood estimation of parameters of signal detection theory: a direct solution. Psychometrika. 1968 ; 33: 117-124.
3. Hanley JA The use of the 'binormal' model for parametric ROC analysis of quantitative diagnostic tests. Stat Med. 1996 ; 15: 1575-1585.
4. Zou KH, Hall WJ Two transformation models for estimating an ROC curve derived from continuous data. J Appl Stat. 2000 ; 27: 621-631.
5. Faraggi D., Reiser B. Estimation of the area under the ROC curve. Stat Med. 2002 ; 30: 3093-3106.
6. Faraggi D. Adjusting ROC curves and related indices for covariates. Statistician. 2003 ; 52: 179-192.
7. Schisterman EF, Faraggi D., Reiser B. Adjusting the generalized ROC curve for covariates. Stat Med. 2004 ; 23: 3319-3331.
8. Metz CE, Herman BA, Shen J. -H. Maximum-likelihood estimation of ROC curves from continuously-distributed data. Stat Med. 1998 ; 17: 1033-1053.
9. Alonzo TA, Pepe MS Distribution-free ROC analysis using binary regression techniques. Biostatistics. 2002 ; 3: 421-432.
10. Dodd L., Pepe MS Semi-parametric regression for the area under the Receiver Operating Characteristic Curve. Jrnl Amer Stat Assoc. 2003 ; 98: 409-417.
11. Pepe MS The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford, UK: Oxford University Press; 2003.
12. Hunink MGM, Richardson DK, Doubilet PM, Begg CB Testing for fetal pulmonary maturity: ROC analysis involving covariates, verification bias, and combination testing. Med Decis Making. 1990 ; 10: 201-211.
13. Pepe MS Three approaches to regression analysis of receiver operating characteristic curves for continuous test results. Biometrics. 1998 ; 54: 124-135.
14. Pepe MS An interpretation for the ROC curve and inference using GLM procedures. Biometrics. 2000 ; 56: 352-359.
15. Cai T., Zheng Y. Model checking for ROC regression analysis. Biometrics. 2007 ; 63: 152-163.
16. Lehmann EL The power of rank tests. Ann Math Stat. 1953 ; 24: 23-43.
17. Le CT Evaluation of confounding effects in ROC studies. Biometrics. 1997 ; 53: 998-1007.
18. Cox DR Regression models and life tables (with discussion). J R Stat Soc B. 1972 ; 34: 187-220.
19. Cox DR Partial likelihood. Biometrika. 1975 ; 62: 269-276.
20. Lin DY, Wei LJ, Ying Z. Checking the Cox model with cumulative sums of Martingale-based residuals. Biometrika. 1993 ; 80: 557-572.
21. Grambsch PM, Therneau TM Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994 ; 81: 515-526.
22. Tosteson AN, Begg CB A general regression methodology for ROC curve estimation. Med Decis Making. 1988 ; 8: 204-215.
23. Lee, EW, Wei, LJ, Amato, DA Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In: Survival Analysis: State of the Art (JP Klein, PK Goel, Eds.). 237-247. Dordrecht: Kluwer Academic Publishers, 1992.
24. Zajick DC, Morrison WB, Schweitzer ME, Parellada JA, Carrino JA Benign and malignant processes: normal values and differentiation with chemical shift MR imaging in vertebral marrow. Radiology. 2005 ; 237: 590-596.
25. Oakes D. The asymptotic information in censored survival data. Biometrika. 1977 ; 64: 441-448.
26. Kalbfleisch JD Likelihood methods and nonparametric tests. J Am Stat Assoc. 1978 ; 73: 167-170.