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Nonparametric inference for the joint distribution of recurrent marked variables and recurrent survival time

Author

Listed:
  • Laura M. Yee

    (U.S. Food and Drug Administration)

  • Kwun Chuen Gary Chan

    (University of Washington)

Abstract

Time between recurrent medical events may be correlated with the cost incurred at each event. As a result, it may be of interest to describe the relationship between recurrent events and recurrent medical costs by estimating a joint distribution. In this paper, we propose a nonparametric estimator for the joint distribution of recurrent events and recurrent medical costs in right-censored data. We also derive the asymptotic variance of our estimator, a test for equality of recurrent marker distributions, and present simulation studies to demonstrate the performance of our point and variance estimators. Our estimator is shown to perform well for a wide range of levels of correlation, demonstrating that our estimators can be employed in a variety of situations when the correlation structure may be unknown in advance. We apply our methods to hospitalization events and their corresponding costs in the second Multicenter Automatic Defibrillator Implantation Trial (MADIT-II), which was a randomized clinical trial studying the effect of implantable cardioverter-defibrillators in preventing ventricular arrhythmia.

Suggested Citation

  • Laura M. Yee & Kwun Chuen Gary Chan, 2017. "Nonparametric inference for the joint distribution of recurrent marked variables and recurrent survival time," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 207-222, April.
    • Handle: RePEc:spr:lifeda:v:23:y:2017:i:2:d:10.1007_s10985-015-9347-7
    DOI: 10.1007/s10985-015-9347-7
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    References listed on IDEAS

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    4. Mei-Cheng Wang & Ying-Qing Chen, 2000. "Nonparametric and Semiparametric Trend Analysis for Stratified Recurrence Times," Biometrics, The International Biometric Society, vol. 56(3), pages 789-794, September.
    5. 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.
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    7. Fang, Hong-Bin & Wang, Jiantian & Deng, Dianliang & Tang, Man-Lai, 2011. "Estimating the mean of a mark variable under right censoring on the basis of a state function," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1726-1735, April.
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