標題: Marginal Regression Analysis for Semi-Competing Risks Data Under Dependent Censoring
作者: Ding, A. Adam
Shi, Guangkai
Wang, Weijing
Hsieh, Jin-Jian
統計學研究所
Institute of Statistics
關鍵字: artificial censoring;log-rank statistic;multiple events data;transformation model
公開日期: 1-九月-2009
摘要: 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.
URI: http://dx.doi.org/10.1111/j.1467-9469.2008.00635.x
http://hdl.handle.net/11536/6723
ISSN: 0303-6898
DOI: 10.1111/j.1467-9469.2008.00635.x
期刊: SCANDINAVIAN JOURNAL OF STATISTICS
Volume: 36
Issue: 3
起始頁: 481
結束頁: 500
顯示於類別:期刊論文


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