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Estimation of Conditional Kendall's Tau for Bivariate Interval Censored Data

  • Kim, Yang-Jin (Department of Statistics, Sookmyung Women's University)
  • Received : 2015.07.13
  • Accepted : 2015.10.06
  • Published : 2015.11.30

Abstract

Kendall's tau statistic has been applied to test an association of bivariate random variables. However, incomplete bivariate data with a truncation and a censoring results in incomparable or unorderable pairs. With such a partial information, Tsai (1990) suggested a conditional tau statistic and a test procedure for a quasi independence that was extended to more diverse cases such as double truncation and a semi-competing risk data. In this paper, we also employed a conditional tau statistic to estimate an association of bivariate interval censored data. The suggested method shows a better result in simulation studies than Betensky and Finkelstein's multiple imputation method except a case in cases with strong associations. The association of incubation time and infection time from an AIDS cohort study is estimated as a real data example.

Keywords

References

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