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Biometrika 2000 87(4):879-893; doi:10.1093/biomet/87.4.879
© 2000 by Biometrika Trust
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On assessing the association for bivariate current status data

Weijing Wang and A. Adam Ding

Institute of Statistics, National Chiao-Tung University, Hsin-Chu, Taiwan, R.O.C. wjwang@stat.nctu.edu.tw Department of Mathematics, Northeastern University, Boston, Massachusetts 02115, U.S.A.ding@neu.edu

Assuming that the two failure times of interest with bivariate current status data follow a bivariate copula model, we propose a two-stage estimation procedure to estimate the association parameter which is related to Kendall's tau. Asymptotic properties of the proposed semiparametric estimator show that, although the first-stage marginal estimators have a convergence rate of only n1/3, the resulting parameter estimator still converges to a normal random variable with the usual n1/2 rate. The variance of the proposed estimator can be consistently estimated. Simulation results are presented, and a community-based study of cardiovascular diseases in Taiwan provides an illustrative example.

Key Words: Copula model; Cross-sectional data; Kendall's tau; Odds ratio; Pseudolikelihood; Semiparametric estimation.


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