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On Testing Dependence between Time to Failure and Cause of Failure when Causes of Failure Are Missing

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  • Isha Dewan
  • Sangita Kulathinal

Abstract

The hypothesis of independence between the failure time and the cause of failure is studied by using the conditional probabilities of failure due to a specific cause given that there is no failure up to certain fixed time. In practice, there are situations when the failure times are available for all units but the causes of failures might be missing for some units. We propose tests based on U-statistics to test for independence of the failure time and the cause of failure in the competing risks model when all the causes of failure cannot be observed. The asymptotic distribution is normal in each case. Simulation studies look at power comparisons for the proposed tests for two families of distributions. The one-sided and the two-sided tests based on Kendall type statistic perform exceedingly well in detecting departures from independence.

Suggested Citation

  • Isha Dewan & Sangita Kulathinal, 2007. "On Testing Dependence between Time to Failure and Cause of Failure when Causes of Failure Are Missing," PLOS ONE, Public Library of Science, vol. 2(12), pages 1-7, December.
    • Handle: RePEc:plo:pone00:0001255
    DOI: 10.1371/journal.pone.0001255
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    References listed on IDEAS

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    1. Isha Dewan & J. V. Deshpande & S. B. Kulathinal, 2004. "On Testing Dependence between Time to Failure and Cause of Failure via Conditional Probabilities," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 79-91, March.
    2. Anup Dewanji & Debasis Sengupta, 2003. "Estimation of Competing Risks with General Missing Pattern in Failure Types," Biometrics, The International Biometric Society, vol. 59(4), pages 1063-1070, December.
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