More info on this will follow soon

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 (ttest, chi², ANOVA...) to further analyses related to the study designs discussed in the first module:

   • Lineair regression
   • Logistic regression (inclusive model validation and diagnostic regression);
   • Poisson regression analysis of time related data (‘event-history’) with attention to Cox proportional hazard modelling.

   Students will also be introduced to longitudinal data analysis.

3. Qualitative study design  – Prof. H. Bastiaens, Prof. S. Anthierens, PhD. G. Tsakitzidis & Prof. dr. Paul Van Royen
   We will explain why and when qualitative research can be used and assess its validity and reliability.
   
   • focus group research
   • interviewing
   • case studies
   • narratives
   • ethnographic research
   • phenomenological research
   
   The students will be able to design their own qualitative study, analyse qualitative data and design and publish qualitative research studies (using NVivo or Atlas software).

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.

5. Health economics and cost-effectiveness - Dr. P. Suykerbuyk
   This lecture will provide insights for performing cost-effectiveness analysis, as well as understanding the issues faced by health economists.

Practical sessions

1. Introduction to the use of statistical packages (R) - PhDc. C. Delgado-Ratto, Msc. S. Nakato & PhDc. L. de Thurah
   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 either 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.

To have an idea of the day-to-day programme during the 6-week course you can download the schedule of the last edition (2018).

"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."