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Median Analysis of Repeated Measures Associated with Recurrent Events in Presence of Terminal Event

Author

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  • Sundaram Rajeshwari

    (Division of Intramural Population Health Research, National Institute of Child Health and Human Development, Rm 3232 6710B Rockledge Dr, Bethesda, MD 20892-2425, USA)

  • Ma Ling

    (Division of Intramural Population Health Research, National Institute of Child Health and Human Development, Rm 3232 6710B Rockledge Dr, Bethesda, MD 20892-2425, USA)

  • Ghoshal Subhashis

    (Department of Statistics, North Carolina State University, Raleigh, NC, USA)

Abstract

Recurrent events are often encountered in medical follow up studies. In addition, such recurrences have other quantities associated with them that are of considerable interest, for instance medical costs of the repeated hospitalizations and tumor size in cancer recurrences. These processes can be viewed as point processes, i.e. processes with arbitrary positive jump at each recurrence. An analysis of the mean function for such point processes have been proposed in the literature. However, such point processes are often skewed, leading to median as a more appropriate measure than the mean. Furthermore, the analysis of recurrent event data is often complicated by the presence of death. We propose a semiparametric model for assessing the effect of covariates on the quantiles of the point processes. We investigate both the finite sample as well as the large sample properties of the proposed estimators. We conclude with a real data analysis of the medical cost associated with the treatment of ovarian cancer.

Suggested Citation

  • 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.
  • Handle: RePEc:bpj:ijbist:v:13:y:2017:i:1:p:16:n:8
    DOI: 10.1515/ijb-2016-0057
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    References listed on IDEAS

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    1. Jianguo Sun & Xingwei Tong & Xin He, 2007. "Regression Analysis of Panel Count Data with Dependent Observation Times," Biometrics, The International Biometric Society, vol. 63(4), pages 1053-1059, December.
    2. Yining Ye & John D. Kalbfleisch & Douglas E. Schaubel, 2007. "Semiparametric Analysis of Correlated Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 63(1), pages 78-87, March.
    3. Chiung-Yu Huang & Mei-Cheng Wang, 2004. "Joint Modeling and Estimation for Recurrent Event Processes and Failure Time Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1153-1165, December.
    4. Lei Liu & Xuelin Huang & John O'Quigley, 2008. "Analysis of Longitudinal Data in the Presence of Informative Observational Times and a Dependent Terminal Event, with Application to Medical Cost Data," Biometrics, The International Biometric Society, vol. 64(3), pages 950-958, September.
    5. D. Y. Lin, 2000. "Proportional Means Regression for Censored Medical Costs," Biometrics, The International Biometric Society, vol. 56(3), pages 775-778, September.
    6. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    7. 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.
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