A semi-parametric joint latent class model with longitudinal and survival data

Yue Liu, Ye Lin, Jianhui Zhou, Lei Liu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In many longitudinal studies, we are interested in both repeated measures of a biomarker and time to an event. When there exist heterogeneous patterns of the longitudinal and survival profiles, we propose a latent class joint model to identify subgroups of subjects and study the association between longitudinal and survival outcomes. The model is estimated by maximizing the full likelihood function. We use B-splines to approximate the baseline hazard function which involves a diverging number of parameters. Asymptotic properties of the estimator for the joint latent class model are investigated. We conduct simulation studies to assess the performance of the developed method. A real data example, Mayo Clinic Primary Biliary Cirrhosis Data, is analyzed using the joint modeling approach.

Original languageEnglish
Pages (from-to)411-422
Number of pages12
JournalStatistics and its Interface
Volume13
Issue number3
DOIs
StatePublished - 2020

Keywords

  • B-splines
  • Longitudinal measurements
  • Mixed effects model
  • Proportional hazards model
  • Survival outcome

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