I am a professor of biostatistics at the Erasmus Medical Center Rotterdam. My research focuses on joint models for longitudinal and time-to-event data with applications in biomarker identification, precision medicine, precision screening and active surveillance. I currently serve as a co-Editor for Biostatistics [twitter handle].
PhD in Biostatistics, 2008
Katholieke Universiteit Leuven
MSc in Statistics, 2004
Athens University of Economics and Business
BSc in Statistics, 2002
Athens University of Economics and Business
Extensions of joint models for improving subject-specific predictions.
Computational methods for multivariate joint models.
Novel methods for optimally planning when to collect longitudinal measurements or event information.
The current composition of my research group:
Pedro Manuel Miranda Afonso: Pedro is a PhD student working on extensions of joint models for recurrent event data and spatial correlations with applications in cystic fibrosis.
Nina van Gerwen: Nina is a PhD student working in causal dynamic predictions using joint models and machine learning.
Aglina Lika: Aglina is a PhD student working in developing methodology and software for Bayesian multivariate mixed effects models.
Fridtjof Petersen: Fridtjof is a PhD student working in extending joint models to the setting of intensive longitudinal data.
Teun Petersen: Teun is a PhD student working in developing new methods for personalized screening with applications in cardiology.
Zhenwei Yang: Zhenwei is a PhD student working on applications of joint models in personalized scheduling with applications in prostate cancer research.
The major R packages I have developed and currently maintain
JMbayes2: Extended Joint Models for Longitudinal and Time-to-Event Data
[GitHub]
[CRAN]
[website]
GLMMadaptive: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature
[GitHub]
[CRAN]
[website]
JMbayes: Joint Models for longitudinal and time-to-event data under a Bayesian approach
[GitHub]
[CRAN]
[JSS paper]
[multivatiate joint Models vignette]
[dynamic predictions vignette]
JM: Joint models for longitudinal and time-to-event data under maximum likelihood
[GitHub]
[CRAN]
[JSS paper]
[Book]
[Book website]
[sample_analysis]
ltm: Latent trait models under the Item Response Theory approach
[GitHub]
[CRAN]
[JSS paper]
[sample_analysis_dichotomous]
[sample_analysis_polytomous1]
[sample_analysis_polytomous2]
[sample_analysis_abilities]
[sample_analysis_information]
cvGEE: Cross-Validated Predictions and Caclulation of Proper Scoring rules for GEE
[GitHub]
[CRAN]
[website]
I am the coordinator for the following courses at Erasmus MC:
Repeated Measurements
In the GitHub repository a shiny app that replicates all analysis in the course
[course link]
[GitHub]
[slides]
Joint Models for Longitudinal and Survival Data
[course link]
[slides]
[solutions_practicals]
Survival Analysis
[course link]
[slides]
[practicals]
[solutions_practicals]
[Survival Analysis in R Companion]
Basic Concepts for Probability and Statistics & Variable Selection [course link] [slides basic concepts] [slides variable selection]
I have also been teaching short-courses in joint modeling in international conferences. A list of recent courses
Wed, Aug 30, 2023, International Society for Clinical Biostatistics Annual Conference
Mon, Aug 28, 2023, International Society for Clinical Biostatistics Annual Conference
Tue, Aug 8, 2023, Joint Statistical Meetings
Wed, Apr 19, 2023, Seminar Department of Health Data Science
Fri, Sep 30, 2022, Data Analytics Workshop: Longitudinal data and time-to-event modeling
I have written the first book on Joint Models for Longitudinal and Survival Data
R-forge website containing the R code to replicate the analysis
A trailer of my inaugural address is available here.
A full list of my publications and grants can be found in my CV.