Partial sufficient dimension reduction on joint model of recurrent and terminal events

  • Weiwei Wang
  • , Xianyi Wu
  • , Xiaoqi Zhang
  • , Xiaobing Zhao*
  • , Xian Zhou
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Joint modeling of recurrent and terminal events has attracted considerable interest and extensive investigations by many authors. The assumption of low-dimensional covariates has been usually applied in the existing studies, which is however inapplicable in many practical situations. In this paper, we consider a partial sufficient dimension reduction approach for a joint model with high-dimensional covariates. Some simulations as well as three real data applications are presented to confirm and assess the performance of the proposed model and approach.

Original languageEnglish
Pages (from-to)522-541
Number of pages20
JournalJournal of Applied Statistics
Volume46
Issue number3
DOIs
StatePublished - 17 Feb 2019

Keywords

  • Joint model
  • high-dimensional
  • partial sufficient dimension reduction
  • recurrent event
  • terminal event

Fingerprint

Dive into the research topics of 'Partial sufficient dimension reduction on joint model of recurrent and terminal events'. Together they form a unique fingerprint.

Cite this