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Semiparametric time-to-event modeling in the presence of a latent progression event
2016
Biometrics
In cancer research, interest frequently centers on factors influencing a latent event that must precede a terminal event. In practice it is often impossible to observe the latent event precisely, making inference about this process difficult. To address this problem, we propose a joint model for the unobserved time to the latent and terminal events, with the two events linked by the baseline hazard. Covariates enter the model parametrically as linear combinations that multiply, respectively,
doi:10.1111/biom.12580
pmid:27556886
pmcid:PMC5325816
fatcat:ya4mwhxjjrcp3igadnhf73o3bi