3 citations · 3 across the 3 of their papers we have counts for
3 papers
A time-varying bivariate copula joint model for longitudinal and time-to-event data
Zili Zhang, Christiana Charalambous, Peter Foster
A time-varying bivariate copula joint model, which models the repeatedly measured longitudinal outcome at each time point and the survival data jointly by both the random effects a…
A Gaussian copula joint model for longitudinal and time-to-event data with random effects
Zili Zhang, Christiana Charalambous, Peter Foster
Longitudinal and survival sub-models are two building blocks for joint modelling of longitudinal and time to event data. Extensive research indicates separate analysis of these two…
Joint modelling of longitudinal measurements and survival times via a multivariate copula approach
Zili Zhang, Christiana Charalambous, Peter Foster
Joint modelling of longitudinal and time-to-event data is usually described by a joint model which uses shared or correlated latent effects to capture associations between the two…