Estimation of the Association for Bivariate Interval-censored Failure Time Data

Multivariate failure time data frequently occur in medical studies and the dependence or association among survival variables is often of interest ("Biometrics", <b>51</b>, 1995, 1384; "Stat. Med.", <b>18</b>, 1999, 3101; "Biometrika", <b>87</b>, 2000, 879; "J. Roy. Statist. Soc. Ser. B", <b>65</b>, 2003, 257). We study the problem of estimating the association between two related survival variables when they follow a copula model and only bivariate interval-censored failure time data are available. For the problem, a two-stage estimation procedure is proposed and the asymptotic properties of the proposed estimator are established. Simulation studies are conducted to assess the finite sample properties of the presented estimate and the results suggest that the method works well for practical situations. An example from an acquired immunodeficiency syndrome clinical trial is discussed. Copyright 2006 Board of the Foundation of the Scandinavian Journal of Statistics..