66th ISI World Statistics Congress

66th ISI World Statistics Congress

Joint models: Advances and software

Organiser

V
Janet Van Niekerk

Participants

  • V
    Prof. Janet Van Niekerk
    (Chair)

  • FG
    Prof. Freedom Gumedze
    (Presenter/Speaker)
  • Joint modelling of longitudinal ordinal data and survival data with competing risks

  • VR
    Virginie Rondeau
    (Presenter/Speaker)
  • Assessing surrogacy from joint modeling and mediation analysis when surrogates are either censored event times or longitudinal biomarker: A cancer application

  • DR
    Denis Rustand
    (Presenter/Speaker)
  • The INLAjoint R package: INLA for complex non-linear multi-outcome and joint modeling

  • M
    Mr Pedro Miranda-Afonso
    (Presenter/Speaker)
  • The JMbayes2 R package for joint models of longitudinal and time-to-event data: From flexible fitting to dynamic prediction and validation

  • EK
    Elias Krainski
    (Presenter/Speaker)
  • The graphpcor R package: Models for correlation matrices with application to graph-based joint modeling

  • Proposal Description

    This proposal is put forth due to the importance and wide applicability of joint models (models for multi-outcome data). These models are inherently complex due to correlation between outcomes and non-linear patters and as such necessitates sophisticated methods and computational approaches, which we plan to demonstrate in this session.
    The speakers are all experts in joint models, approached from differing viewpoints and contributing valuable different views. The speakers and the chair vary in location to present an international profile and offer a balance between genders (although not perfectly balanced).
    Invited sessions on joint models are usually very well attended by Academia and the industry, especially the pharmaceutical industry.

    I believe that this session can contribute significantly to the high quality of the program and stimulating new research in joint models, while enriching the audience's knowledge and curiosities.