1
Vol. 2, NoI' 1, January 1995 GENERALIZING THE ROC ANALYSIS ples is conducted, representativeness of our samples cannot be assumed. Thus, although we have identified some problems, there is no way to determine the rela- tive frequency with which these problems will occur. ACKNOWLEDGMENT This work is supported in part by grant numbers CA58283 and CA60259 from the National Cancer Institute. REFERENCES 1. Swets JA, Pickett RM. Evaluation of diagnostic systems: methods from signal detection theo~ New York: Academic Press, 1982:46-93. 2. Turner DA. An intuitive approach to receiver operating characteristic curve analysis. J Nucl Med 1978; 19:213-220. 3. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148:839-843. 4. Metz CE. Some practical issues of experimental design and data analysis in radiological ROC studies. Invest Radio11989; 24:234-245. 5. Chakraborty DP. Maximum likelihood analysis of free-response receiver operating characteristic analyses. Med Phys 1989;16:561-568. 6. Rockette HE, Gur D, Cooperstein LA, et al. Effect of two rating formats in multi-disease ROC study of chest images. Invest Radio11999;25:225-229. 7. Agresti A. A model for agreement between ratings on an ordinal scale. Biometrics 1988;44:539-548. 8. Wieand S, Gail MH, James BR, James KL. A family of nonparametfic sta- tistics for comparing diagnostic markers with paired or unpaired data. Biometrika 1989;76:585-592. 9. Lams PM, Cocklin ME Spatial resolution requirements for digital chest radiographs: An ROC study of observer performance in selected cases. Radiology 1986;158:11-19. 10. MacMahon, Vyborny CJ, Metz CE, et al. Digital radiography of subtle pul- monary abnormalities: An ROC study of the effect of pixel size on observer performance. Radiology1986;158:21-26. 11. Slasky BS, Gur D, Good WF, et al. ROC analysis of chest image interpre- tation on conventional radiographs, laser-printed radiographs, and high- resolution workstation. Radiology 1990; 174:775-780. 12. Cox GG, Cook LT, McMillan JH, et al. Chest radiography: comparison of high-resolution digital displays with conventional and digital film. Radiology 1990; 176:771-776. 13. Dorfman DD, Berbaum KS, Metz CE. Receiver operating characteristic rating analysis: Generalization to the population of readers and patients with the jackknife method. Invest Radio11992;27:723-731. 14. Metz CE, Shen J-H, Herman BA. Newmethods for estimating a binormal ROC curve from continuously-distributed test results. Paper presented at the 1990 Joint Statistical Meetings of the American Statistical Society and the Biometric Society; August 1990; Anaheim, CA. 15. Tukey JW. Bias and confidence in not-quite large samples. Ann Math Statist 1958;29:614. Abstract. 16. Efron B, Tibshirani RJ. An Introduction to the Bootstrap. Chapman & Hall: London, 1993:145. 17. Arvesen JN. Jackknifing U-statistics. Ann Math Statist1969;40:2076-2100. 18. Arvesen JN, Schmitz TH. Robust procedures for variance component problems using the jackknife. Biometrics 1970;26:677-686. 19. McClish DK. Comparing the areas under more than two independent ROC curves. Med Decis Making 1987;7:149-155. Announcement The UCLA General Radiology Review Course will be held March 5-10, 1995, at the Guest Quarters Suite Hotel in Santa Monica, CA. Forty hours of Category 1 credit will be awarded (pending). The cost is $420. For more informa- tion, contact Darry Bailey, UCLAMedical Center, Department of Radiological Sciences, 10833 Le Conte Ave., B2-170 CHS, Los Angeles, CA 90024-1721; (310) 825-8763; fax (310) 206-5725. 69

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Page 1: Announcement

Vol. 2, NoI' 1, January 1995 G E N E R A L I Z I N G T H E R O C A N A L Y S I S

ples is conducted, representativeness of our samples cannot be assumed. Thus, although we have identified some problems, there is no way to determine the rela- tive frequency with which these problems will occur.

A C K N O W L E D G M E N T

This work is supported in part by grant numbers CA58283 and CA60259 from the National Cancer Institute.

REFERENCES

1. Swets JA, Pickett RM. Evaluation of diagnostic systems: methods from signal detection theo~ New York: Academic Press, 1982:46-93.

2. Turner DA. An intuitive approach to receiver operating characteristic curve analysis. J Nucl Med 1978; 19:213-220.

3. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148:839-843.

4. Metz CE. Some practical issues of experimental design and data analysis in radiological ROC studies. Invest Radio11989; 24:234-245.

5. Chakraborty DP. Maximum likelihood analysis of free-response receiver operating characteristic analyses. Med Phys 1989;16:561-568.

6. Rockette HE, Gur D, Cooperstein LA, et al. Effect of two rating formats in multi-disease ROC study of chest images. Invest Radio11999;25:225-229.

7. Agresti A. A model for agreement between ratings on an ordinal scale. Biometrics 1988;44:539-548.

8. Wieand S, Gail MH, James BR, James KL. A family of nonparametfic sta- tistics for comparing diagnostic markers with paired or unpaired data. Biometrika 1989;76:585-592.

9. Lams PM, Cocklin ME Spatial resolution requirements for digital chest radiographs: An ROC study of observer performance in selected cases. Radiology 1986;158:11-19.

10. MacMahon, Vyborny C J, Metz CE, et al. Digital radiography of subtle pul- monary abnormalities: An ROC study of the effect of pixel size on observer performance. Radiology1986;158:21-26.

11. Slasky BS, Gur D, Good WF, et al. ROC analysis of chest image interpre- tation on conventional radiographs, laser-printed radiographs, and high- resolution workstation. Radiology 1990; 174:775-780.

12. Cox GG, Cook LT, McMillan JH, et al. Chest radiography: comparison of high-resolution digital displays with conventional and digital film. Radiology 1990; 176:771-776.

13. Dorfman DD, Berbaum KS, Metz CE. Receiver operating characteristic rating analysis: Generalization to the population of readers and patients with the jackknife method. Invest Radio11992;27:723-731.

14. Metz CE, Shen J-H, Herman BA. Newmethods for estimating a binormal ROC curve from continuously-distributed test results. Paper presented at the 1990 Joint Statistical Meetings of the American Statistical Society and the Biometric Society; August 1990; Anaheim, CA.

15. Tukey JW. Bias and confidence in not-quite large samples. Ann Math Statist 1958;29:614. Abstract.

16. Efron B, Tibshirani RJ. An Introduction to the Bootstrap. Chapman & Hall: London, 1993:145.

17. Arvesen JN. Jackknifing U-statistics. Ann Math Statist1969;40:2076-2100. 18. Arvesen JN, Schmitz TH. Robust procedures for variance component

problems using the jackknife. Biometrics 1970;26:677-686. 19. McClish DK. Comparing the areas under more than two independent

ROC curves. Med Decis Making 1987;7:149-155.

A n n o u n c e m e n t

The UCLA General Radiology Review Course will be held March 5-10, 1995, at the Guest Quarters Suite Hotel in Santa Monica, CA. Forty hours of Category 1 credit will be awarded (pending). The cost is $420. For more informa- tion, contact Darry Bailey, UCLA Medical Center, Department of Radiological Sciences, 10833 Le Conte Ave., B2-170 CHS, Los Angeles, CA 90024-1721; (310) 825-8763; fax (310) 206-5725.

69