Extended Joint Models for Longitudinal & Time-to-event Data: with applications in Cardiothoracic Surgery

Research output: Types of ThesisDoctoral ThesisInternal

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Abstract


In this thesis, we developed extensions for the joint modeling framework for longitudinal and time-to-event data, motivated by various clinical research questions in cardiothoracic surgery. These extensions focus in the handling of intermediate events during follow-up, feature selection in multivariate settings such as multiple longitudinal outcomes and multi-state processes using Bayesian shrinkage priors and sensitivity analysis for missing data under the joint modeling framework.
Original languageEnglish
Awarding Institution
  • Erasmus University Rotterdam
Supervisors/Advisors
  • Rizopoulos, Dimitris, Supervisor
  • Takkenberg, Hanneke, Supervisor
  • Mokhles, Mostafa, Co-supervisor
Award date14 Dec 2021
Place of PublicationRotterdam
Print ISBNs978-94-6419-351-0
Publication statusPublished - 14 Dec 2021

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