| Summary: | 碩士 === 國立中正大學 === 數學系統計科學研究所 === 103 === This paper investigates the quantile residual life regression based on semi-competing risk data. Because the non-terminal event time is dependently censored by the terminal event time, we can't make inference on the non-terminal event time without extra assumption. Therefore, we assume that the non-terminal event time and the terminal event time follow an Archimedean copula. Then, we apply to the inverse probability weight technique to constructing an estimating equation of quantile residual life regression coefficients. But, the estimating equation may not be continuous in coefficients. Thus, we apply the generalized solution approach to overcoming this problem. Since the variance of the proposed estimator is too difficult to estimate, we use the bootstrap resampling method to estimate it. From the simulation studies, it shows that the performance of the proposed method is well. Finally, we analyze the Bone Marrow Transplant data for illustrations.
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