Modelling longitudinal and time-to-event data: a phase IV simulation study comparing R package implementations of joint models with time-varying Cox proportional-hazards regression, and the two-stage approach

Abstract Joint models offer an unbiased statistical approach for analyzing the effects of longitudinal biomarkers on time-to-event outcomes, providing an alternative to time-varying Cox proportional-hazards regression and the two-stage approach. However, whether available implementations of these me...

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Autores principales:	Jil Heege, Sonja Greven, Elke Schaeffner, Ulrike Grittner, Annette Aigner
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	BMC 2026-05-01
Colección:	BMC Medical Research Methodology
Materias:	Joint models Two-stage approach Longitudinal data Time-varying covariates Time-to-event analysis Simulation study
Acceso en línea:	https://doi.org/10.1186/s12874-026-02875-4
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