Pre-course preparation


A short description of the tasks and their estimated workload is given below. The topics have been spread over three months. Once selected for the course, you will obtain access to the pre-course material.

Epidemiology - July

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Biostatistics - August

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Qualitative research methods - September

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Programme summary

Major topics

  1. Quantitative study design – Prof. J. Weyler
    Principles of prognostic (cohort), etiologic (case-control) and diagnostic (cross-sectional) research will be explained with a focus on study object, data collection (design methods) and data analysis. In addition, more recent design types will be presented as case-cohort, case-cross-over studies. The participants will be able to select the best research design taking into account the specific context (domain) and the specific research question (etiognostic, diagnostic, prognostic).

  2. Methods of data analysis/biostatistics – Prof. S. Abrams
    Analysis of scientific data will gradually progress from basics (t-test, chi², ANOVA...) to further analyses related to the study designs discussed in the first module:

    Linear regression
    Generalized linear regression (logistic and Poisson regression)
    Cox proportional hazards regression

    Students will also be introduced to longitudinal data analysis and missing data techniques.

  3. Qualitative study design  – Prof. dr. H. Bastiaens, Prof. dr. S. Anthierens and QUALUA-team
    In this basic course on qualitative research, we will focus on the principles, design, conducting, evaluating the quality and reporting of qualitative research. We will combine theory and hands-on practice. After the course students will be able to set up and conduct their own qualitative research in a scientifically rigorous way.

  4. Systematic reviews and Meta-analysis  – PhD. N. Pauwels & PhD. E. Deschepper
    The course will teach the different steps to take to perform a high-quality, methodologically sound and reliable systematic review and meta-analysis. The course is filled with workshops preparing the participant to get immediately started with his/her own systematic review and meta-analysis.

Practical sessions

  1. Introduction to the use of statistical packages (R) - PhD. C. Delgado-Ratto
    The students will learn how to use R software during hands-on statistics exercises with databases. The practical lessons on descriptive and inferential statistics will provide the basis to comprehensibly analyze their own databases using any of this software package.

  2. Research Project (R & Nvivo) – Prof. J.-P. Van geertruyden & colleagues
    Students will conduct their own data analysis.Depending on the research topic, the student may analyse quantitative or qualitative data, perform a meta-analysis or perform a cost-effectiveness analysis. Study analysis will be presented by the students throughout the sessions and results will finally be presented in a congress style session at the end of the course. (Tutoring possible in English, French, Spanish, and Dutch)

A Certificate of Attendance will be awarded after completion of the course.


Day-to-day programme

To have an idea of the day-to-day programme during the 6-week course you can download the schedule of the last edition (2019).



"The EBQ helps participants to make sense of the basic statistics and epidemiology designs encountered in research. In my own view every clinician should undertake EBQ so as to improve clinical care by applying research findings."


"I recommend the EBQ because it is very practical, pertinent, relevant and we were able to study practicing.


I would recommend the course to phd students who are interested in implementation of research results because I’ve learned a lot on this. Students are exposed to what needs to be done in the real world.”


"This course presents more advantages compared to others. First, we get training on two types of research: qualitative and quantitative. Second, the research project allows participants to apply what has been taught and to receive feedback on the design, analysis, etc. on various themes. Third, the research project is individual; each participant can work under supervision of the tutor. Fourth, we work on issues which are real on the ground, we can find solutions for the problems and we can even publish."