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Smoothed empirical likelihood for ROC curves with censored data

Listed author(s):
  • Yang, Hanfang
  • Zhao, Yichuan
Registered author(s):

    The receiver operating characteristic (ROC) curve is an attractive basis for the comparison of distribution functions between two populations. In this paper, we apply the censored empirical likelihood method with kernel smoothing to investigate the ROC curve. It is shown that the smoothed empirical likelihood ratio converges to a chi-square distribution, which is the well-known Wilks theorem. We also propose a bootstrap procedure for obtaining the censored empirical likelihood confidence band for the ROC curve. The performance of the proposed empirical likelihood method is illustrated through extensive simulation studies in terms of coverage probability and average length of confidence intervals.

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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 109 (2012)
    Issue (Month): C ()
    Pages: 254-263

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    Handle: RePEc:eee:jmvana:v:109:y:2012:i:c:p:254-263
    DOI: 10.1016/j.jmva.2012.03.002
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    1. Shen, Junshan & He, Shuyuan, 2006. "Empirical likelihood for the difference of two survival functions under right censorship," Statistics & Probability Letters, Elsevier, vol. 76(2), pages 169-181, January.
    2. Zhao, Yichuan & Zhao, Meng, 2011. "Empirical likelihood for the contrast of two hazard functions with right censoring," Statistics & Probability Letters, Elsevier, vol. 81(3), pages 392-401, March.
    3. Einmahl, J.H.J. & McKeague, I.W., 1999. "Confidence tubes for multiple quantile plots via empirical likelihood," Other publications TiSEM b64493f8-1c01-40fd-b16d-7, Tilburg University, School of Economics and Management.
    4. Lloyd, Chris J. & Yong, Zhou, 1999. "Kernel estimators of the ROC curve are better than empirical," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 221-228, September.
    5. Horváth, Lajos, 1983. "The rate of strong uniform consistency for the multivariate product-limit estimator," Journal of Multivariate Analysis, Elsevier, vol. 13(1), pages 202-209, March.
    6. Diehl, Sabine & Stute, Winfried, 1988. "Kernel density and hazard function estimation in the presence of censoring," Journal of Multivariate Analysis, Elsevier, vol. 25(2), pages 299-310, May.
    7. Li, Gang, 1995. "On nonparametric likelihood ratio estimation of survival probabilities for censored data," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 95-104, November.
    8. McKeague, Ian W. & Zhao, Yichuan, 2002. "Simultaneous confidence bands for ratios of survival functions via empirical likelihood," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 405-415, December.
    9. McKeague, Ian W. & Zhao, Yichuan, 2006. "Width-scaled confidence bands for survival functions," Statistics & Probability Letters, Elsevier, vol. 76(4), pages 327-339, February.
    10. Junshan Shen & Shuyuan He, 2007. "Empirical likelihood for the difference of quantiles under censorship," Statistical Papers, Springer, vol. 48(3), pages 437-457, September.
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