3 citations · 3 across the 5 of their papers we have counts for
5 papers
A general joint latent class model of longitudinal and survival data with the covariance modelling
Ruoyu Miao, Christiana Charalambous
Based on the proposed time-varying JLCM (Miao and Charalambous, 2022), the heterogeneous random covariance matrix can also be considered, and a regression submodel for the variance…
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 joint latent class model of longitudinal and survival data with a time-varying membership probability
Ruoyu Miao, Christiana Charalambous
Joint latent class modelling has been developed considerably in the past two decades. In some instances, the models are linked by the latent class k (i.e. the number of subgroups),…
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…