A conditional nonparametric test for comparing two areas under the ROC curves from a paired design

被引:7
|
作者
Bandos, AI [1 ]
Rockette, HE
Gur, D
机构
[1] Univ Pittsburgh, Grad Sch Publ Hlth, Dept Biostat, Pittsburgh, PA 15261 USA
[2] Univ Pittsburgh, Sch Med, Dept Radiol, Pittsburgh, PA 15261 USA
关键词
observer performance; ROC; technology assessment;
D O I
10.1016/j.acra.2004.08.013
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Rationale and Objectives. To develop a conditional nonparametric procedure for comparing two correlated areas under receiver operating characteristic (ROC) curves (AUC). Materials and Methods. A nonparametric conditional test to compare areas under two ROC curves was developed using the distribution of the elements of the nonparametric AUC estimators in a permutation space. The conditioning is made on the observed discordances between the relative orderings of ratings of the normal and abnormal cases for the two modalities taken over all possible pairs. The type I error of the procedure was verified using computer simulations. The power of the test was compared with an existing unconditional procedure on simulated datasets from binormal distributions as well as from a mixture of binormal distributions of ratings. Results. The proposed test is conservative for low sample sizes, large AUC, and high correlation between modalities. It possesses a reasonable type I error for sample sizes as low as 20 actually positive and 20 actually negative cases. In plausible situations in which the sample in observer performance studies can not be monotonically transformed into a binormal distribution, this approach may have modest power advantages over the conventional nonparametric test. Conclusion. The conditional nonparametric test presented here is an alternative approach to existing unconditional procedures and may offer advantages in certain types of observer performance studies.
引用
收藏
页码:291 / 297
页数:7
相关论文
共 50 条
  • [1] A permutation test sensitive to differences in areas for comparing ROC curves from a paired design
    Bandos, AI
    Rockette, HE
    Gur, D
    [J]. STATISTICS IN MEDICINE, 2005, 24 (18) : 2873 - 2893
  • [2] A modified sign test for comparing paired ROC curves
    Braun, Thomas M.
    Alonzo, Todd A.
    [J]. BIOSTATISTICS, 2008, 9 (02) : 364 - 372
  • [3] A test for comparing conditional ROC curves with multidimensional covariates
    Fanjul-Hevia, A.
    Pardo-Fernandez, J. C.
    Van Keilegom, I
    Gonzalez-Manteiga, W.
    [J]. JOURNAL OF APPLIED STATISTICS, 2022,
  • [4] A test for comparing conditional ROC curves with multidimensional covariates
    Fanjul-Hevia, A.
    Pardo-Fernandez, J. C.
    Van Keilegom, I.
    Gonzalez-Manteiga, W.
    [J]. JOURNAL OF APPLIED STATISTICS, 2024, 51 (01) : 87 - 113
  • [5] A non-parametric test for comparing conditional ROC curves
    Fanjul-Hevia, Aris
    Gonzalez-Manteiga, Wenceslao
    Pardo-Fernandez, Juan Carlos
    [J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2021, 157 (157)
  • [6] A NONPARAMETRIC APPROACH FOR PARTIAL AREAS UNDER ROC CURVES AND ORDINAL DOMINANCE CURVES
    Yang, Hanfang
    Lu, Kun
    Zhao, Yichuan
    [J]. STATISTICA SINICA, 2017, 27 (01) : 357 - 371
  • [7] Interval estimation for the difference in paired areas under the ROC curves in the absence of a gold standard test
    Hsieh, Hsin-Neng
    Su, Hsiu-Yuan
    Zhou, Xiao-Hua
    [J]. STATISTICS IN MEDICINE, 2009, 28 (25) : 3108 - 3123
  • [8] A non-inferiority test of areas under two parametric ROC curves
    Jin, Hua
    Lu, Ying
    [J]. CONTEMPORARY CLINICAL TRIALS, 2009, 30 (04) : 375 - 379
  • [9] On the exact interval estimation for the difference in paired areas under the ROC curves
    Li, Chi-Rong
    Liao, Chen-Tuo
    Liu, Jen-Pei
    [J]. STATISTICS IN MEDICINE, 2008, 27 (02) : 224 - 242
  • [10] A non-inferiority test for diagnostic accuracy based on the paired partial areas under ROC curves
    Li, Chi-Rong
    Liao, Chen-Tuo
    Liu, Jen-Pei
    [J]. STATISTICS IN MEDICINE, 2008, 27 (10) : 1762 - 1776