Browsing by Author "Ding, AA"

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On assessing the association for bivariate current status data
(2000-12-01)
Wang, WJ
;
Ding, AA
;
統計學研究所
;
Institute of Statistics
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 n(1/3), the resulting parameter estimator still converges to a normal random variable with the usual n(1/2) 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.
Testing independence for bivariate current status data
(2004-03-01)
Ding, AA
;
Wang, WJ
;
統計學研究所
;
Institute of Statistics
This article develops a nonparametric procedure for testing marginal independence based on bivariate current status data. Asymptotic properties of the proposed tests are derived, and their finite-sample performance is studied via simulations. The method is applied to analyze data from a community-based study of cardiovascular epidemiology in Taiwan.