Projects

Individualized Predictions, Time-varying Effects and Time-varying Covariates

Extensions of joint models for improving subject-specific predictions.

Multivariate Joint Models

Computational methods for multivariate joint models.

Personalized Active Surveillance and Screening

Novel methods for optimally planning when to collect longitudinal measurements or event information.

People

The current composition of my research group:

  • Pedro Manuel Miranda Afonso: Pedro works on extensions of joint models for recurrent event data and spatial correlations with applications in cystic fibrosis.

  • Arnau Garcia Fernandez: Arnau works in combinations of joint models and machine learning.

  • Nina van Gerwen: Nina works in causal dynamic predictions using joint models and machine learning.

  • Aglina Lika: Aglina works in developing methodology and software for Bayesian multivariate mixed effects models.

  • Fridtjof Petersen: Fridtjof works in extending joint models to the setting of intensive longitudinal data.

  • Zhenwei Yang: Zhenwei works on applications of joint models in personalized scheduling with applications in prostate cancer research.

Software

The major R packages I have developed and currently maintain

Teaching

I am the coordinator for the following courses at Erasmus MC:

I have also been teaching short-courses in joint modeling in international conferences. A list of recent courses

Recent & Upcoming Talks

More Talks

Recent Publications

More Publications

  • Optimizing personalized screening intervals for clinical biomarkers using extended joint models

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  • Personalized biopsy schedules using an interval-censored cause-specific joint model

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  • Predicting dropout in intensive longitudinal data: Extending the joint model for auto-correlated data

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  • Risk-profile based monitoring intervals for multivariate longitudinal biomarker measurements and competing events with applications in stable heart failure

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  • A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data

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  • Using joint models for longitudinal and time-to-event data to investigate the causal effect of salvage therapy after prostatectomy

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  • Optimizing Dynamic Predictions from Joint Models using Super Learning

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  • Sample size calculation for clinical trials analyzed with the meta-analytic-predictive approach

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  • Modeling the underlying biological processes in Alzheimer's disease using a multivariate competing risk joint model

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  • Shared decision making of burdensome surveillance tests using personalized schedules and their burden and benefit

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Book

I have written the first book on Joint Models for Longitudinal and Survival Data

Book-Cover

Inaugural Speech

A trailer of my inaugural address is available here.

CV

A full list of my publications and grants can be found in my CV.

Contact