Incorporating latent survival trajectories and covariate heterogeneity in time-to-event data analysis: a joint mixture model approach
The proposed joint model effectively identifies latent subgroups, revealing unobserved heterogeneity in survival outcomes and prognostic factors. Its flexibility enables more precise estimation of survival trajectories, with broad applicability in survival analysis.
Authors
- Wenyaw Chan (ORCID: https://orcid.org/0000-0003-3329-5282)
- Fu‐Wen Liang (ORCID: https://orcid.org/0000-0002-3396-037X)
- Michael D. Swartz (ORCID: https://orcid.org/0000-0003-3953-8775)
- Bouthaina S. Dabaja
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- Kaohsiung Medical University (TW)
- Kaohsiung Medical University Chung-Ho Memorial Hospital (TW)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1186/s12874-025-02580-8
- Citations
- 1
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- Ministry of Science and Technology, Taiwan
- National Science and Technology Council