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Empirical-likelihood-based semiparametric inference for the treatment effect in the two-sample problem with censoring

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  • Yong Zhou
  • Hua Liang

Abstract

To compare two samples of censored data, we propose a unified method of semi-parametric inference for the parameter of interest when the model for one sample is parametric and that for the other is nonparametric. The parameter of interest may represent, for example, a comparison of means, or survival probabilities. The confidence interval derived from the semiparametric inference, which is based on the empirical likelihood principle, improves its counterpart constructed from the common estimating equation. The empirical likelihood ratio is shown to be asymptotically chi-squared. Simulation experiments illustrate that the method based on the empirical likelihood substantially outperforms the method based on the estimating equation. A real dataset is analysed. Copyright 2005, Oxford University Press.

Suggested Citation

  • Yong Zhou & Hua Liang, 2005. "Empirical-likelihood-based semiparametric inference for the treatment effect in the two-sample problem with censoring," Biometrika, Biometrika Trust, vol. 92(2), pages 271-282, June.
    • Handle: RePEc:oup:biomet:v:92:y:2005:i:2:p:271-282
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    File URL: http://hdl.handle.net/10.1093/biomet/92.2.271
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    Cited by:

    1. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1520-1531, July.
    2. Jiang, Shan & Tu, Dongsheng, 2012. "Inference on the probability P(T1," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1069-1078.
    3. Francesco Bravo & David Jacho-Chavez, 2011. "Empirical Likelihood for Efficient Semiparametric Average Treatment Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 1-24.
    4. Lin, Cunjie & Zhou, Yong, 2014. "Inference for the treatment effects in two sample problems with right-censored and length-biased data," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 17-24.
    5. Li Xun & Li Tao & Yong Zhou, 2020. "Estimators of quantile difference between two samples with length-biased and right-censored data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 409-429, June.
    6. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.

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