Biostatistics Unit

Objectives

The primary purpose of the Biostatistics Unit of the Faculty of Medicine and Health Sciences of Ghent University is to deliver statistical advice and services to researchers of this faculty and the Ghent University Hospital. This implies advice with respect to study design, choice of appropriate statistical methods, sample size and power issues, support in data analyses, interpreting results, etc...

The Biostatistics Unit further organizes internal courses and training sessions dedicated to specific statistical methods and software.

Contact

Ellen Deschepper, PhD, Roos Colman, Stefanie De Buyser, PhD & Ineke van Gremberghe, Phd
UZ-campus, Corneel Heymanslaan 10, 4K3, B-9000 Ghent, Belgium
Phone : 09 332 52 99/ 09 332 83 06/ 09 332 19 61/ 09 332 21 82
E-mail : statcel@UGent.be (research) or statcel.thesis@UGent.be (master thesis)

Directions

The Biostatistics Unit is located at the Ghent University Hospital, Corneel Heymanslaan 10, 4K3, building K3 (Entrance 42) on the 4th floor. You can find the Biostatistics Unit in room 140.029.

Statistical Support of Master Theses

Recently, an online E-learning site is created on Ufora: "E-learning Statistics". This Statistics e-learning site is a realization of the Biostatistics Unit (Cel Biostatistiek) and the statistics lecturers (lerend netwerk lesgevers statistiek) of the Faculty of Medicine and Health Sciences, to support statistics education and scientific research. This site includes a statistical test finder, various statistical modules and good practices. It aims to be a practical guide to support students and researchers in performing their statistical analyses in SPSS and R. All members of the faculty of medicine and health sciences have automatically access to this Ufora course: E-Learning Statistiek Faculteit Geneeskunde en Gezondheidswetenschappen - Statistics Faculty of Medicine and Health Sciences - DX00115. Please note that the statistics e-learning site is still under construction.

When questions remain unsolved after consulting the E-learning site and student’s own course materials, due to

• missing statistical methodology as this site is still under construction
• the complexity of the design, research questions or statistical methodology
• the setup of a new prospective study
• …

the Biostatistics Unit can be consulted by the promotor and his/her students. To make an appointment for the support of Master theses, send an e-mail to statcel.thesis@ugent.be. It is mandatory that the promotor joins the student during the consults.

Courses and Training Sessions

The Biostatistics Unit of the Faculty of Medicine and Health Sciences offers several courses. The following courses are taught in English:

Causal Reasoning and Inference: Moving Beyond ‘Correlation Is Not Causation’: September-October 2026 (English)

‘Correlation does not imply causation’, a phrase you’ve likely heard repeatedly during your statistical training. Although a legitimate scientific goal, researchers are often discouraged from asking causal questions because, as reviewers and editors emphasize, these questions cannot be answered reliably without experimentation or randomization. As a result, researchers commonly use statistical approaches that estimate ‘adjusted associations’, tend to avoid explicit causal language when interpreting these measures, yet often conclude their manuscripts with policy recommendations that are implicitly grounded in causal interpretations.

Advances in the interdisciplinary field of causal inference show that we can do better and that being explicit about causal study goals helps to avoid common errors and reduce bias. For example, the usual—but often unstated—goal of multivariate regression is to produce estimates adjusted for confounders to make causal interpretations more justifiable. Many researchers were, however, never taught that standard regression adjustment practices are usually inappropriate to answer the (usually implicit) causal question(s) of interest and often increase, rather than reduce, bias. In addition, not only confouning bias, but also other forms of bias—less familiar to many researchers—lurk around the corner, even though they can usually be prevented.

This course will focus on common pitfalls and how to avoid them by aligning causal goals with causal reasoning and appropriate causal methods. You’ll be introduced to key theoretical concepts—such as counterfactual outcomes—and practical tools, including causal DAGs, to strengthen causal reasoning. The course also covers the basics of implementing causal methods, such as g-computation, in R.

Start using R: February-March 2027 (English)

 Would you, as a researcher in health sciences, like to conduct and report your analyses in a reproducible way? Would you like to visualize your results in high-quality figures? Are you interested in learning how to program in R, but unsure how to get started? Then this course is for you.

This course is recognized as a Specialist Course by the UGent Doctoral School. When requesting funding, the application for recognition must be submitted no later than one month before the start of the course. Our courses are also included in the Faculty Research Training Program of the Faculty of Medicine and Health Sciences.

Cancellation policy

The following cancellation policy applies to the above courses.