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Robust empirical likelihood inference for longitudinal data

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  • Qin, Guoyou
  • Bai, Yang
  • Zhu, Zhongyi

Abstract

This paper introduces the robust empirical likelihood (REL) inference for the longitudinal data. We propose the REL method by constructing robust auxiliary random vectors, and employ bounded scores and leverage-based weights in the auxiliary random vectors to achieve robustness against outliers in both the response and covariates. Simulation studies are conducted to demonstrate the good performance of our proposed REL method in terms of both robustness and efficiency improvement. The proposed method is also illustrated by analyzing a real data set from epileptic seizure study.

Suggested Citation

  • Qin, Guoyou & Bai, Yang & Zhu, Zhongyi, 2009. "Robust empirical likelihood inference for longitudinal data," Statistics & Probability Letters, Elsevier, vol. 79(20), pages 2101-2108, October.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:20:p:2101-2108
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    References listed on IDEAS

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    1. He, Xuming & Fung, Wing K. & Zhu, Zhongyi, 2005. "Robust Estimation in Generalized Partial Linear Models for Clustered Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1176-1184, December.
    2. Glenn, N.L. & Zhao, Yichuan, 2007. "Weighted empirical likelihood estimates and their robustness properties," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5130-5141, June.
    3. Liugen Xue & Lixing Zhu, 2007. "Empirical Likelihood Semiparametric Regression Analysis for Longitudinal Data," Biometrika, Biometrika Trust, vol. 94(4), pages 921-937.
    4. You-Gan Wang & Xu Lin & Min Zhu, 2005. "Robust Estimating Functions and Bias Correction for Longitudinal Data Analysis," Biometrics, The International Biometric Society, vol. 61(3), pages 684-691, September.
    5. Sinha S.K., 2004. "Robust Analysis of Generalized Linear Mixed Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 451-460, January.
    6. Cantoni E. & Ronchetti E., 2001. "Robust Inference for Generalized Linear Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1022-1030, September.
    7. Kelvin K. W. Yau & Anthony Y. C. Kuk, 2002. "Robust estimation in generalized linear mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(1), pages 101-117, January.
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    Cited by:

    1. Qin, Guoyou & Bai, Yang & Zhu, Zhongyi, 2012. "Robust empirical likelihood inference for generalized partial linear models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 32-44.
    2. Xing-cai Zhou & Jin-Guan Lin, 2014. "Empirical likelihood for varying-coefficient semiparametric mixed-effects errors-in-variables models with longitudinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 51-69, March.
    3. Li, Shaomin & Wang, Kangning & Ren, Yanyan, 2018. "Robust estimation and empirical likelihood inference with exponential squared loss for panel data models," Economics Letters, Elsevier, vol. 164(C), pages 19-23.

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