Dependence Model Selection for Semi-Competing Risks Data

• 作者: Cheng-Fang Tsai Jin-Jian Hsieh
• 来源期刊: 统计学期刊(英文)
• 学科: 工学
• 关键词: Copula MODEL LIKELIHOOD Function MODEL Selection Semi-Competing RISKS DATA
• 年，卷（期）: 2020,（2）
• 页码范围: 228-238
• 页数: 11页
• 分类号: TP3

摘要

We consider the model selection problem of the dependency between the?terminal event and the non-terminal event under semi-competing risks data. When the relationship between the two events is unspecified, the inference on the non-terminal event is not identifiable. We cannot make inference on the non-terminal event without extra assumptions. Thus, an association model for?semi-competing risks data is necessary, and it is important to select an appropriate dependence model for a data set. We construct the likelihood function for semi-competing risks data to select an appropriate dependence model. From?simulation studies, it shows the performance of the proposed approach is well. Finally, we apply our method to a bone marrow transplant data set.