Causality in Quantitative Research

Target audience

PhD candidates in social sciences

Organizing and scientific committee

Lisa Janssen

Lore Baeten

Prof. Dr. Anna Kern


For many social scientists, establishing causal relationships constitutes a core research objective. Yet, for all its scientific importance, causal inference presents social scientists with tremendous challenges to overcome. This specialized course will provide an overview of the various quantitative research designs that attempt to uncover causal relationships. The course combines theoretical discussions of the Potential Outcomes Framework and counterfactuals with concrete examples of different quantitative research designs. These include, amongst others, instrumental variable approaches, regression discontinuity designs, time-series regressions, and (quasi-) experiments.


After completion of the course, students will have acquired the following skills:

  • Students will have in-depth knowledge of the concept of causality as featured in empirical social science research, including knowledge about the Potential Outcomes Framework and counterfactuals.
  • Students will have the capacity to translate causal research questions and objectives into quantitative research designs that are suitable for causal inference.
  • Students will be able to critically evaluate the internal validity of quantitative social science research.
  • Students will get familiar with and understand varying quantitative research designs suitable for causal inference, such as experiments, instrumental variables, and time-series regressions.
  • Students will be able to identify possible threats to the internal validity of their own research, as well as learn how to overcome them

Dates and venue

18 - 20 December 2023, Technicum 2 (venue to be confirmed)


Day 1: 4 hours – Lectures with discussion and practical exercises

  • 13:00 – 15:00 Lecture on the logic of causal inference and the meaning of causality. Discussion on the difference between causation and correlation. Introduction to the Potential Outcomes Framework and thinking about counterfactuals.
  • 15:00 – 17:00 Tutorial on randomized experiments and experimental designs. Participants will discuss suitable experimental designs for a given research question in groups. They will also think about how the Potential Outcomes Framework applies to these experiments.

Day 2: 8 hours – Lectures with discussion and practical exercises

  • 9:00 – 10:00 Recap of previous day. Room for questions.
  • 10:00 – 12:30 Lecture on causality in regression. We will also discuss how causality applies to moderation/interaction effects.
  • 13:00 – 15:30 Tutorial where participants will practice with causal graphs and will think about whether to add certain control variables or not.
  • 15:30 – 17:30 Lecture on time-series analyses. How can causality be established using, for instance, panel data?

Day 3: 8 hours – Lectures with discussion and practical exercises

  • 9:00 – 10:00 Recap of the previous day. Room for questions.
  • 10:00 – 12:00 Tutorial in which participants will think about how they can apply time series analyses to their own research ideas.
  • 12:30 – 14:30 Lecture on quasi-experimental methods, regression discontinuity designs and instrumental variables estimation.
  • 14:40 – 16:30 Tutorial in which participants will look at studies that apply quasi-experimental methods and discuss the internal validity and potential flaws of these studies. Participants will discuss in groups how these studies could be improved.
  • 16:30 – 17:30 Wrapping up the course. What are the main takeaways and explanation about proposal assignment.


Follow this link for the registration and waiting list. 

Cancellation of your registration can only be performed by sending an email to

Registration fee

Free of charge for Doctoral School members.

The no show policy applies.

Number of participants

Maximum 20



Training method

Lectures with discussions and practical exercises

Evaluation method

To complete the course, students need 100% attendance. Moreover, students will have the option to hand in an original research proposal. For this assignment, students are expected to apply the themes of the course to their own research. The research proposal outlines a research question, hypotheses and, most importantly, a research design capable of empirically testing the causal expectations set forth in the theory section. Students will be provided feedback on their proposal by the lecturer, so that they can improve the internal validity of their study. 

After successful participation, the Doctoral Schools will add this course to your curriculum of the Doctoral Training Programme in Oasis. Please note that this can take up to one to two months after completion of the course.