Programme

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. 

Starting the EBQ in Antwerp, you will have an entrance exam with questions regarding to the material shared during the pre-EBQ.

Epidemiology - July

Task description: 

Assignment 1. Update your knowledge with respect to the measures of occurrence (incidence, prevalence) adding the concepts of ‘events’ and ‘states’ as well as the temporal aspects (current future)

Assignment 2. Read (study) ‘Miettinen OS. The modern scientific physician: 2. Medical science versus scientific medicine.

Assignment 3. Read (study) ‘Miettinen OS. The modern scientific physician: 7. Theory of medicine

Total workload: 10 hours

Biostatistics - August

Task description: 

Assignment 1: Introduction to R (data camp course + exercises); workload: 4 hours.

Assignment 2: Descriptive statistics: part I (video + exercises); workload: 1 hour (video) + 1 hour (exercises)

Assignment 3: Descriptive statistics: part II (video + exercises); workload: 1 hour (video) + 1 hour (exercises)

Total workload: 

8 hours

Qualitative research methods - September

Task description: 

Short video’s with questions: max. workload 2 hours

3 articles + questions : max. workload 8 hours

Total workload: 10 hours

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 analyze 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.

Eligible participants for admission to the EBQ course:

Researchers/PhD students from different disciplines and faculties are accepted. In order to guarantee a personal progress trajectory and interactive exchanges during classes. 

A maximum of 20 participants will be accepted  for each edition.

Requirements:

• Master's Degree
• Basic knowledge of epidemiology (level Beaglehole; ISBN 978 92 4 154707 9)
• Basic Essential Medical Statistics (level part A & B Kirkwood, ISBN 978 0 86542871 3)
• Excellent command of English (upper intermediate level)
• Good knowledge of Microsoft Office software
• Own dataset
• Personal laptop