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Empirical likelihood inference for semi-parametric transformation models with length-biased sampling

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  • Yu, Xue
  • Zhao, Yichuan

Abstract

The semi-parametric transformation models under length-biased sampling are considered. The well-known proportional hazards model and proportional odds model are special cases of the semi-parametric transformation models. Empirical likelihood and adjusted empirical likelihood inferences for semi-parametric transformation models with length-biased sampling are proposed, and the empirical log-likelihood ratio test statistic is shown to converge to a standard chi-squared distribution. In addition, statistical inferences for the regression parameters are made based on the results. Moreover, extensive simulation studies are carried out. Finally, a real data set is analyzed to illustrate the proposed empirical likelihood and adjusted empirical likelihood methods.

Suggested Citation

  • Yu, Xue & Zhao, Yichuan, 2019. "Empirical likelihood inference for semi-parametric transformation models with length-biased sampling," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 115-125.
    • Handle: RePEc:eee:csdana:v:132:y:2019:i:c:p:115-125
    DOI: 10.1016/j.csda.2018.10.012
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    References listed on IDEAS

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    11. Hui-Ling Lin & Zhouping Li & Dongliang Wang & Yichuan Zhao, 2017. "Jackknife empirical likelihood for the error variance in linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 151-166, April.
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