Dimitris Rizopoulos

Latest

• A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data.
• Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data.
• Association between changes in pulmonary function and in patient reported outcomes during enzyme therapy of adult patients with late-onset Pompe disease
• Computerised patient-specific prediction of the recovery profile of upper limb capacity within stroke services. The next step.
• Reflections on modern methods. Dynamic prediction using joint models of longitudinal and time-to-event data.
• A Bayesian joint model for zero-inflated integers and left-truncated event times with a time-varying association. Applications to senior health care.
• Integrating Latent Classes in the Bayesian Shared Parameter Joint Model of Longitudinal and Survival Outcomes.
• Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using P-splines.
• Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures.
• Combined dynamic predictions using joint models of two longitudinal outcomes and competing risk data.
• Joint modeling of two longitudinal outcomes and competing risk data.
• An introduction to mixed models and joint modeling: analysis of valve function over time.