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Empirical likelihood analysis of the rank estimator for the censored accelerated failure time model


  • Mai Zhou


We use the empirical likelihood method to derive a test and thus a confidence interval based on the rank estimators of the regression coefficient in the accelerated failure time model. Standard chi-squared distributions are used to calculate the p-value and to construct the confidence interval. Simulations and examples show that the chi-squared approximation to the distribution of the log empirical likelihood ratio performs well, and has some advantages over the existing methods. Copyright 2005, Oxford University Press.

Suggested Citation

  • Mai Zhou, 2005. "Empirical likelihood analysis of the rank estimator for the censored accelerated failure time model," Biometrika, Biometrika Trust, vol. 92(2), pages 492-498, June.
  • Handle: RePEc:oup:biomet:v:92:y:2005:i:2:p:492-498

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    References listed on IDEAS

    1. Kai-tai Fang & Rahul Mukerjee, 2005. "Expected lengths of confidence intervals based on empirical discrepancy statistics," Biometrika, Biometrika Trust, vol. 92(2), pages 499-503, June.
    2. 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.
    3. Kai-Tai Fang & Rahul Mukerjee, 2006. "Empirical-type likelihoods allowing posterior credible sets with frequentist validity: Higher-order asymptotics," Biometrika, Biometrika Trust, vol. 93(3), pages 723-733, September.
    4. Nicole A. Lazar, 2003. "Bayesian empirical likelihood," Biometrika, Biometrika Trust, vol. 90(2), pages 319-326, June.
    5. T. J. Sweeting, 1999. "On the construction of Bayes-confidence regions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 849-861.
    6. Francesco Bravo, 2003. "Second-order power comparisons for a class of nonparametric likelihood-based tests," Biometrika, Biometrika Trust, vol. 90(4), pages 881-890, December.
    7. Susanne M. Schennach, 2005. "Bayesian exponentially tilted empirical likelihood," Biometrika, Biometrika Trust, vol. 92(1), pages 31-46, March.
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    Cited by:

    1. Yang, Song & Zhao, Yichuan, 2007. "Testing treatment effect by combining weighted log-rank tests and using empirical likelihood," Statistics & Probability Letters, Elsevier, vol. 77(12), pages 1385-1393, July.
    2. Ming Zheng & Wen Yu, 2013. "Empirical likelihood method for multivariate Cox regression," Computational Statistics, Springer, vol. 28(3), pages 1241-1267, June.
    3. Yu, Lili & Peace, Karl E., 2012. "Spline nonparametric quasi-likelihood regression within the frame of the accelerated failure time model," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2675-2687.
    4. Lili Yu & Liang Liu & Ding-Geng(Din) Chen, 2013. "Weighted Least-Squares Method for Right-Censored Data in Accelerated Failure Time Model," Biometrics, The International Biometric Society, vol. 69(2), pages 358-365, June.
    5. Wen Yu & Yunting Sun & Ming Zheng, 2011. "Empirical likelihood method for linear transformation models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 331-346, April.
    6. Wanrong Liu & Xuewen Lu, 2011. "Empirical likelihood for density-weighted average derivatives," Statistical Papers, Springer, vol. 52(2), pages 391-412, May.
    7. Zhao, Yichuan, 2011. "Empirical likelihood inference for the accelerated failure time model," Statistics & Probability Letters, Elsevier, vol. 81(5), pages 603-610, May.
    8. Shen, Junshan & Yuen, Kam Chuen & Liu, Chunling, 2016. "Empirical likelihood confidence regions for one- or two- samples with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 285-293.
    9. Mu Zhao & Yixin Wang & Yong Zhou, 2016. "Accelerated failure time model with quantile information," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(5), pages 1001-1024, October.
    10. Tong Tong Wu & Gang Li & Chengyong Tang, 2015. "Empirical Likelihood for Censored Linear Regression and Variable Selection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 798-812, September.
    11. Yuan, Ao & Xu, Jinfeng & Zheng, Gang, 2012. "Root-n estimability of some missing data models," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 147-166.
    12. Cheng, Jung-Yu & Tzeng, Shinn-Jia, 2009. "Parametric and semiparametric methods for mapping quantitative trait loci," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1843-1849, March.

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