2023-2024 / STAT0007-1

Advanced statistics in epidemiology


10h Th, 10h Pr

Number of credits

 Master in public health (120 ECTS) (Transitional programme)5 crédits 
 Master in public health (120 ECTS) (new programme)2 crédits 
 University certificate in clinical epidemiology and healthcare economics2 crédits 


Anne-Françoise Donneau

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course consists of an in-depth study of multivariate statistical methods (in particular, the binary logistic regression) and the impact on these methods of problems encourtered on real data as well as the possible solutions. The course will focus on the following themes:

  • Introduction to SAS
  • Binary logistic regression
  • ROC curve
  • Potential confounding factors
  • Quality of models
  • Automatic variable selection 
  • Missing data

Learning outcomes of the learning unit

The objective of the course is to introduce, practically, multivariate statistical methods frequently used in epidemiology. At the end of the course, the student must be able to present the problem, apply the analysis using the SAS software and expose clearly the derived results .He must also be able to understand the presentation of multivariate methods in the scientific literature.

Prerequisite knowledge and skills

Prerequisite: STAT1750-1 or good knowledge of multivariate statistical analysis.

Planned learning activities and teaching methods

The practical sessions consist in analysing mulltivariate datasets by means of the statistical package SAS.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course

Additional information:

Each course will switch between theory and practice with the SAS software. One lesson will be dedicated to an introduction of this software.

Recommended or required readings

Slides as well as databases used during the courses will be made available to the students.

Written work / report

Additional information:

Written work

Work placement(s)

Organisational remarks and main changes to the course


* Anne-Françoise DONNEAU (Professor), Quartier Hôpital, Avenue Hippocrate, 13 - Bât 23, 4000 Liège - Belgique. Tél: 04-366.47.90 Email: afdonneau@uliege.be

 * Assistante : Nadia DARDENNE, Quartier Hôpital, Avenue Hippocrate, 13 - Bât 23, 4000 Liège - Belgique - Tél: 04-366.33.40 - Email: ndardenne@uliege.be


Association of one or more MOOCs