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A rank-based empirical likelihood approach to two-sample proportional odds model and its goodness of fit

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  • Zhong Guan
  • Cheng Peng

Abstract

A rank-based empirical likelihood method is proposed and applied to estimate the proportionality parameter and the underlying distributions in a two-sample semiparametric proportional odds model. A distribution-free goodness-of-fit test for the model is also given. It is proved that the maximum likelihood estimator of the proportionality parameter is reciprocal symmetric. As one of the applications, we use the proposed procedure to estimate receiver operating characteristic (ROC) curves. We also perform a simulation study to assess the performance of the proposed procedure and provide a numerical example based on real-world data to illustrate the implementation of the method.

Suggested Citation

  • Zhong Guan & Cheng Peng, 2011. "A rank-based empirical likelihood approach to two-sample proportional odds model and its goodness of fit," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 763-780.
    • Handle: RePEc:taf:gnstxx:v:23:y:2011:i:3:p:763-780
    DOI: 10.1080/10485252.2011.559726
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    References listed on IDEAS

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    1. A. N. Pettitt, 1984. "Proportional Odds Models for Survival Data and Estimates Using Ranks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(2), pages 169-175, June.
    2. Jing Qin, 2003. "Using logistic regression procedures for estimating receiver operating characteristic curves," Biometrika, Biometrika Trust, vol. 90(3), pages 585-596, September.
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    Cited by:

    1. Ramesh Gupta & Cheng Peng, 2014. "Proportional odds frailty model and stochastic comparisons," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 897-912, October.

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