Open Journal of Statistics

Volume 10, Issue 2 (April 2020)

ISSN Print: 2161-718X   ISSN Online: 2161-7198

Google-based Impact Factor: 0.53  Citations  

Dependence Model Selection for Semi-Competing Risks Data

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DOI: 10.4236/ojs.2020.102016    388 Downloads   1,206 Views  Citations

ABSTRACT

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.

Share and Cite:

Hsieh, J. and Tsai, C. (2020) Dependence Model Selection for Semi-Competing Risks Data. Open Journal of Statistics, 10, 228-238. doi: 10.4236/ojs.2020.102016.
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