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Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring

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  • Debashis Ghosh
  • D. Y. Lin

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  • Debashis Ghosh & D. Y. Lin, 2003. "Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(4), pages 877-885, December.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:4:p:877-885
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2003.00102.x
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    References listed on IDEAS

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    1. Debashis Ghosh & D. Y. Lin, 2000. "Nonparametric Analysis of Recurrent Events and Death," Biometrics, The International Biometric Society, vol. 56(2), pages 554-562, June.
    2. Wang M-C. & Qin J. & Chiang C-T., 2001. "Analyzing Recurrent Event Data With Informative Censoring," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1057-1065, September.
    3. J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate‐dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
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    Cited by:

    1. Qing Pan & Douglas E. Schaubel, 2009. "Flexible Estimation of Differences in Treatment-Specific Recurrent Event Means in the Presence of a Terminating Event," Biometrics, The International Biometric Society, vol. 65(3), pages 753-761, September.
    2. Xingqiu Zhao & Jie Zhou & Liuquan Sun, 2011. "Semiparametric Transformation Models with Time-Varying Coefficients for Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 67(2), pages 404-414, June.
    3. Gongjun Xu & Sy Han Chiou & Chiung-Yu Huang & Mei-Cheng Wang & Jun Yan, 2017. "Joint Scale-Change Models for Recurrent Events and Failure Time," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 794-805, April.
    4. C.-Y. Huang & J. Qin & M.-C. Wang, 2010. "Semiparametric Analysis for Recurrent Event Data with Time-Dependent Covariates and Informative Censoring," Biometrics, The International Biometric Society, vol. 66(1), pages 39-49, March.
    5. Giuliana Cortese & Thomas H. Scheike, 2022. "Efficient estimation of the marginal mean of recurrent events," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1787-1821, November.
    6. Sy Han Chiou & Gongjun Xu & Jun Yan & Chiung‐Yu Huang, 2018. "Semiparametric estimation of the accelerated mean model with panel count data under informative examination times," Biometrics, The International Biometric Society, vol. 74(3), pages 944-953, September.
    7. Shuling Liu & Amita K. Manatunga & Limin Peng & Michele Marcus, 2017. "A joint modeling approach for multivariate survival data with random length," Biometrics, The International Biometric Society, vol. 73(2), pages 666-677, June.
    8. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
    9. A. Adam Ding & Guangkai Shi & Weijing Wang & Jin‐Jian Hsieh, 2009. "Marginal Regression Analysis for Semi‐Competing Risks Data Under Dependent Censoring," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 481-500, September.
    10. Qing Cai & Mei‐Cheng Wang & Kwun Chuen Gary Chan, 2017. "Joint modeling of longitudinal, recurrent events and failure time data for survivor's population," Biometrics, The International Biometric Society, vol. 73(4), pages 1150-1160, December.
    11. Sundaram Rajeshwari & Ma Ling & Ghoshal Subhashis, 2017. "Median Analysis of Repeated Measures Associated with Recurrent Events in Presence of Terminal Event," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-16, May.
    12. Jean‐Yves Dauxois & Sophie Sencey, 2009. "Non‐parametric Tests for Recurrent Events under Competing Risks," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 649-670, December.
    13. Huazhen Lin & Ling Zhou & Chunhong Li & Yi Li, 2014. "Semiparametric transformation models for semicompeting survival data," Biometrics, The International Biometric Society, vol. 70(3), pages 599-607, September.
    14. Shigeyuki Matsui, 2004. "Analysis of Times to Repeated Events in Two-Arm Randomized Trials with Noncompliance and Dependent Censoring," Biometrics, The International Biometric Society, vol. 60(4), pages 965-976, December.
    15. Jin-Jian Hsieh & A. Adam Ding & Weijing Wang, 2011. "Regression Analysis for Recurrent Events Data under Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(3), pages 719-729, September.
    16. Richard Tawiah & Geoffrey J. McLachlan & Shu Kay Ng, 2020. "A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction," Biometrics, The International Biometric Society, vol. 76(3), pages 753-766, September.
    17. Youngjoo Cho & Debashis Ghosh, 2015. "Weighted Estimation of the Accelerated Failure Time Model in the Presence of Dependent Censoring," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-22, April.
    18. Marie Böhnstedt & Jutta Gampe & Monique A. A. Caljouw & Hein Putter, 2023. "Incorporating delayed entry into the joint frailty model for recurrent events and a terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 585-607, July.
    19. Ding, A. Adam, 2010. "Identifiability conditions for covariate effects model on survival times under informative censoring," Statistics & Probability Letters, Elsevier, vol. 80(11-12), pages 911-915, June.

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