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The department of Biostatistics develops novel statistical models and procedures that are motivated and applied in clinical, epidemiological and public health research and practice.

About our Department

Our research

The current areas of active research of the department cover the following topics:

- Longitudinal Data Analysis & Hierarchical Modeling

- Survival Analysis

- Joint Modeling of Longitudinal and Time-to-Event Data

- Statistical Analysis with Missing Data

- Modern Analysis of Clinical Trials

- Bioinformatics and Statistical Genetics

- Growth Curves

- Smoothing Techniques

- Bayesian Modeling

Our Staff

Our Staff Assistant:

Ms. Eline van Gent - e.vangent@erasmusmc.nl 
Biostatistics Secretarial Office - secretariat.biostatistics@erasmusmc.nl 
Absent on Wednesday

Principal Investigators

Project Leaders

Research Lines

Individualized Dynamic Predictions:

Individualized predictions play a key role in precision medicine and shared decision making. Joint models for longitudinal and survival data have been shown to be a valuable tool in this context. In this research line we study and explore different types of extensions of joint models that can improve the quality of the derived predictions.


Personalized Active Surveillance and Screening

Decision making in medicine has become increasingly complex for patients and practitioners. This has resulted from factors such as the shift away from physician authority toward shared decision making, unfiltered information on the Internet, new technology providing additional data, numerous treatment options with associated risks and benefits, and results from new clinical studies. Within this context medical screening procedures are routinely performed for several diseases. In general, the aim of screening procedures is to optimize the benefits, i.e., early detection of disease or deterioration of the condition of a patient, while also balancing the respective costs.

In this research line we develop novel techniques for optimally choosing when to collect biomarker information for patients in a screening phase, and when to plan an invasive procedure. The key element of these techniques is their personalized and dynamic nature, i.e., they suitably adapt utilizing the available information on a patient.


Statistical Analysis with Missing Data

The statistical analysis of almost any type of data collected in human health research is complicated from incomplete information. Even though researchers would like to obtain specific measurements from the study participants, very often this information is missing. In this research line we develop new statistical analysis techniques that allow to make the optimal use of the available data and derive the most useful and relevant conclusions.


Novel Analysis of Clinical Trials

Clinical trials are the primary tool for evaluating the efficacy and safety of new medications and procedures. However, to achieve these results clinical trial typically require enrolling many patients. In this research line we develop novel methodology for analyzing clinical trials using information from previous studies, and hence decreasing the required number of patients to be enrolled.


Books & Dissertations



Head Department of Biostatistics

Prof.dr. Dimitris Rizopoulos



Dr Elrozy Andrinopoulou

Prof.dr.Lidia Arends

Dr Sara Baart

Prof.dr. Bettina Hansen

Dr Sten Willemsen

Emeriti Biostatistics

Prof.dr.Emmanuel Lesaffre

Prof.dr.ing.Paul Eilers

Dr. Wim Hop






Assistant Professor in Biostatistics

Establish a new research line in the intersecting of biostatistics, causal inference and machine learning. Join our team!

Assistant Professor in Biostatistics | Werken bij Erasmus MC


News, events and awards

Our news

6 September 2019, Inaugural Lecture - prof. dr. Dimitris Rizopoulos

1 April 2019, dr. E.R. Andrinopoulou Promoted to Assistant Professor


Kersverse prof. Bettina Hansen pleit voor internationale samenwerking op zeldzame ziekten

Een zeldzame ziekte onderzoek je niet alleen - Erasmus MC


Tobias Polak in de JAMA over expanded acces-onderzoek

‘Behandeling via expanded access? Denk na over data-verzameling’ - Erasmus MC


International Biometric Society (IBC)

International Society for Bayesian Analysis (ISBA)

International Society for Clinical Biostatistics (ISCB)

Joint Statistical Meetings (JSM)



Year Name Conference Award Presentation / Poster
 2024   Pedro Miranda Afonso
 IWSM 38th  Durham Summer Grant 2024  A joint model for multiple longitudinal markers, competing risks, and recurrent events
 2023  Anirudh Tomer 

 Biometry Award - VVSOR

 Hans van Houwelingen award   Shared decision making of burdensome surveillance tests using personalized schedules and their burden and benefit 
 2023  Zhenwei Yang


 Student Conference Award  A Bayesian Joint Modelling for Misclassified Interval-censoring and Competing Risks
 2023  Pedro Miranda Afonso  ISCB 44th  Student Conference Award  A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using registry data
 2023  Pedro Miranda Afonso  SPE 25  Student Travel Grant  A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events
 2023  Pedro Miranda Afonso  SPE 25th  Statistical Portuguese Society Award 2023  A Bayesian shared-parameter approach to jointly model multiple Gaussian and non-Gaussian longitudinal markers with correlated event times
 2018  Anirudh Tomer  EMR - IBS  Student Conference Award - EMR - IBS 10th  Personalized schedules for surveillance of low risk prostate cancer patients
 2018  Anirudh Tomer  IBC  2nd Best oral speaker - IBC 2018  Personalized schedules for surveillance of low risk prostate cancer patients
 2016  Nicole Erler  ISCB  Student Conference Award - ISCB 37th  Bayesian imputation of time-varying covariates in linear mixed models
 2015  Kazem Nasserinejad  EMR - IBS  EMR Student Schlarship - EMR - IBS 8th  Latent Class Mixed-Effects Transition Model: A model to predict hemoglobin in blood donors
 2015  Nicole Erler  EMR - IBS  Student Conference Award - EMR - IBS 8th  Missing Covariates in Epidemiologic Studies: MI vs. a Full Bayesian Approach
 2014  Eleni Rosalina Andrinopoulou  SAM  Poster Award - SAM 2nd  Combined Dynamic Predictions Using Joint Models of Multiple Longitudinal Outcomes and Competing Risk Data
 2014  Eleni Rosalina Andrinopoulou  ISCB  Student Confrence Award - ISCB 35rd  Combined Dynamic Predictions Using Joint Models of Multiple Longitudinal Outcomes and Competing Risk Data
 2012  Magdalena Murawska  ISCB  Student Conference Award - ISCB 33rd  Dynamic Prediction Based on Joint Model for Categorical Response and Time-to-Event
2012  Eleni Rosalina Andrinopoulou  IWSM  Extraordinary Student Oral Presentaion - IWSM 27th  Joint Modeling of Two Longitudinal Outcomes and Competing Risk Data. An Application in Cardio Data.

Any questions?

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