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Empirical likelihood based on synthetic right censored data

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  • Liang, Wei
  • Dai, Hongsheng

Abstract

In this paper, we develop a Mean Empirical Likelihood (MeanEL) method for right censored data. This MeanEL approach is based on traditional empirical likelihood methods but uses synthetic data to construct an EL ratio statistics, which is shown to have a χ2 limiting distribution. Different simulation studies show that the MeanEL confidence intervals tend to have more accurate coverage probabilities than other existing Empirical Likelihood methods. Theoretical comparisons of different EL methods are also provided under a general framework.

Suggested Citation

  • Liang, Wei & Dai, Hongsheng, 2021. "Empirical likelihood based on synthetic right censored data," Statistics & Probability Letters, Elsevier, vol. 169(C).
    • Handle: RePEc:eee:stapro:v:169:y:2021:i:c:s0167715220302650
    DOI: 10.1016/j.spl.2020.108962
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    References listed on IDEAS

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    1. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    2. Qi-Hua Wang & Bing-Yi Jing, 2001. "Empirical Likelihood for a Class of Functionals of Survival Distribution with Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(3), pages 517-527, September.
    3. Liang, Wei & Dai, Hongsheng & He, Shuyuan, 2019. "Mean Empirical Likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 155-169.
    4. Shuyuan He & Wei Liang & Junshan Shen & Grace Yang, 2016. "Empirical Likelihood for Right Censored Lifetime Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 646-655, April.
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