Incorporating latent survival trajectories and covariate heterogeneity in time-to-event data analysis: a joint mixture model approach

Incorporating latent survival trajectories and covariate heterogeneity in time-to-event data analysis: a joint mixture model approach

Abstract Background Finite mixture models have been recently applied in time-to-event data to identify subgroups with distinct hazard functions, yet they often assume differing covariate effects on failure times across latent classes but homogeneous covariate distributions. This study aimed to devel...

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Bibliographic Details
Main Authors: Fu-Wen Liang, Wenyaw Chan, Michael D. Swartz, Bouthaina S. Dabaja
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Medical Research Methodology
Subjects:
Joint modeling
Mixture models
Time-to-event data
Latent class analysis
Survival trajectories
Unobserved heterogeneity
Online Access:https://doi.org/10.1186/s12874-025-02580-8
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https://doi.org/10.1186/s12874-025-02580-8

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