… In this article, we consider this modeling framework and focus particularly on the … a fitted
joint model. Following we derive accuracy measures under the joint modeling framework and …

… We start by defining a set of joint models based on which predictions will be calculated. For
the longitudinal process, we allow a flexible specification of the subject-specific square root …

… by contrasting landmark and joint models for dynamic prediction in the context of a … model.
In Section 2, we introduce notation for landmark and joint models and derive their predicted …

… The most recent extensions and implementations in the literature of dynamic predictions
using joint models have been derived under the Bayesian framework. This approach facilitates …

… This article illustrated how dynamic predictions from joint models with different … model
averaging. The novel feature of this approach is that the weights for combining predictions depend …

… In this section, we demonstrate dynamic prediction based on our flexible joint model. In
particular, we exemplify it by making predictions on the conditional probabilities of surviving the …

… dynamically updated predictions of both survival and freedom from re-intervention for future
patients. In this paper, we propose to jointly model … and derive the dynamically updated …

… dynamic prediction via multivariate joint models and compare the prognostic performance of
these models to both static and univariate joint models. … the dynamic models. A multivariate …

… First we develop a reference nonlinear joint model on a training dataset, second we simulate
mCRPC patients to evaluate dynamic predictions when the model is known and last we …

… to genetic factors and dynamic tumour … joint frailty-copula model to a model allowing for
high-dimensional genetic factors. In addition, we propose a dynamic prediction formula to predict …