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Semiparametric mixed-effects models for clustered doubly censored data

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  • Pao-Sheng Shen

Abstract

The Cox proportional frailty model with a random effect has been proposed for the analysis of right-censored data which consist of a large number of small clusters of correlated failure time observations. For right-censored data, Cai et al. [3] proposed a class of semiparametric mixed-effects models which provides useful alternatives to the Cox model. We demonstrate that the approach of Cai et al. [3] can be used to analyze clustered doubly censored data when both left- and right-censoring variables are always observed. The asymptotic properties of the proposed estimator are derived. A simulation study is conducted to investigate the performance of the proposed estimator.

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  • Pao-Sheng Shen, 2012. "Semiparametric mixed-effects models for clustered doubly censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1881-1892, April.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:9:p:1881-1892
    DOI: 10.1080/02664763.2012.684874
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    1. Cai T. & Cheng S.C. & Wei L.J., 2002. "Semiparametric Mixed-Effects Models for Clustered Failure Time Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 514-522, June.
    2. T. Cai, 2004. "Semiparametric regression analysis for doubly censored data," Biometrika, Biometrika Trust, vol. 91(2), pages 277-290, June.
    3. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 241-278.
    4. Kani Chen, 2002. "Semiparametric analysis of transformation models with censored data," Biometrika, Biometrika Trust, vol. 89(3), pages 659-668, August.
    5. Kelly, Patrick J., 2004. "A Review of Software Packages for Analyzing Correlated Survival Data," The American Statistician, American Statistical Association, vol. 58, pages 337-342, November.
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    1. Pao-sheng Shen, 2014. "Semiparametric regression analysis for clustered doubly-censored data," Computational Statistics, Springer, vol. 29(3), pages 813-828, June.

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