Analysis of Clustered Multivariate Competing Risks Data with High-Dimensional Covariates

  • Takeshi, Emura (PI)

Project: National Science and Technology CouncilNational Science and Technology Council Academic Grants

Project Details


The objective of my research proposal is to create new competing risks analysis methods that can deal with clustered multivariate survival times together with high-dimensional covariates. Existing methodologies are mostly focused on two dimensional competing risks and are not enough to deal with complex survival data obtained from real medical studies. This 3-year project has a plan to develop statistical methods for analyzing 3 different types of data structures, one type for each year. Each data structure needs novel applications of copulas that have never been considered in the literature. In addition, every year handles the issue of high-dimensional covariates that will also be discussed in this proposal.

Project IDs

Project ID:PA10901-0188
External Project ID:MOST107-2118-M182-001-MY3
Effective start/end date01/08/2031/07/21


  • Survival analysis
  • Gene expression
  • Cox model
  • Censoring
  • Copula


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