Module 13: Propensity Score Methods

Type of Course - Dates - Venue - Description - Target audience - Exam - IMPORTANT: Incorporation in DTP and reimbursement by DS
Course prerequisites - Teacher - Course material - Fees - Enrol

Type of course

This is an on campus course. However, should safety restrictions issued by UGent due to the corona crisis make on campus classes impossible, the course will instead be taught online.


Wednesday June 2 and Thursday June 3, 2021, from 9 am to 4 pm and Friday June 4, 2021, from 9 am to 12 pm. (Dates subject to change)
Please note: The deadline for UGent PhD students who want a refund to open a dossier on the DS website (Application for Recognition) is April 30, 2021.


Faculty of Science, Site Sterre, Krijgslaan 281, building S9, Ghent, lecture room 3.1 (V2), third floor + pc class 3.1 (=Konrad Zuse).


The course will consist of the following parts:

Part 1: Introduction. We discuss the basic principles of causal inference; the formulation of a causal question for a well-defined population of interest, an outcome that corresponds to the scientific question under study and a treatment/exposure with relevant levels. We also discuss the problem of confounding by indication and the traditional methods to deal with confounding such as stratification and regression methods.

Part 2: Building a propensity score. The general principle of a propensity score as a balancing score is considered. Methods to build a propensity score, which variables to include.  We discuss how to assess if a propensity score is adequate, the assumption of non-positivity and how it can be checked using a propensity score.

Part 3: Propensity based analysis. Different propensity score methods are discussed: matching, stratification, adjustment in a regression model and inverse probability weighting. Each of the methods is discussed in detail with specific focus on the decisions which have to be made when applying a method to real life data. Several case studies will be discussed.

Part 4. Comparison of the different propensity methods and other methods to deal with confounding, discussion of the advantages and disadvantages, and discussion of the causal estimand which is estimated by each of the methods.

The course will be a mixture of theory, case studies and computer exercises using R or Stata.

Target audience

This course will benefit professionals and investigators who are involved in the comparison of interventions using observational data.


Participants can, if they wish, take part in an exam. Upon succeeding in this test a certificate from Ghent University will be issued.

Please note: For UGent PhD students it is no longer necessary to participate/succeed in this exam to be able to incorporate the course in the DTP.

Incorporation in DTP and reimbursement from DS for UGent PhD students

As a UGent PhD student, to be able to incorporate this 'specialist course' in your Doctoral Training Program (DTP) and get a reimbursement of the registration fee from your Doctoral School (DS) you need to follow strict rules: please take the necessary action in time. The deadline to open a dossier on the DS website (Application for Recognition) for this course is April 30, 2021. Please note that opening a dossier does not mean that you are enrolled. You still need to enrol via the registration form on this site.

Course prerequisites

Participants are expected to have an active knowledge of regression models, in particular logistic regression, and have some experience in working with R or Stata.


Photo Saskia le CessieProfessor Saskia le Cessie is a statistician working at the department of Clinical Epidemiology and Biomedical Data Sciences of Leiden University Medical Centre in Leiden, the Netherlands and is a visiting professor at Ghent University.  The focus of her research is on epidemiological and statistical methods for observational studies. This includes causality in observational studies, mediation analysis,  instrumental variable analysis, meta-analysis and prediction models. Besides methodological research, she actively collaborates in research projects of epidemiologists and other (bio)medical researchers in order to provide cutting edge statistical analyses in observational studies. She is an experienced teacher and has taught courses in bachelor and master programs in the medical and statistical field and national and international post-doctoral courses for medical researchers, epidemiologists and statisticians.

Course material

The presentations and exercises will be available online.


A different price applies, depending on your main type of employment.

EmploymentModule 13
Industry/Private sector1 925
Non-profit, government, university outside AUGent2 785
(Doctoral)student outside AUGent2 355

1 If three or more employees from the same company enrol simultaneously for this course a reduction of 10% on the module price is taken into account.

2 AUGent-staff and AUGent doctoral students who pay through use of an SAP internal order/invoice can participate at these special rates.

Enrol for this course