Browsing by Author "Shi, Guangkai"

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Marginal Regression Analysis for Semi-Competing Risks Data Under Dependent Censoring
(2009-09-01)
Ding, A. Adam
;
Shi, Guangkai
;
Wang, Weijing
;
Hsieh, Jin-Jian
;
統計學研究所
Multiple events data are commonly seen in medical applications. There are two types of events, namely terminal and non-terminal. Statistical analysis for non-terminal events is complicated due to dependent censoring. Consequently, joint modelling and inference are often needed to avoid the problem of non-identifiability. This article considers regression analysis for multiple events data with major interest in a non-terminal event such as disease progression. We generalize the technique of artificial censoring, which is a popular way to handle dependent censoring, under flexible model assumptions on the two types of events. The proposed method is applied to analyse a data set of bone marrow transplantation.