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Causal Mediation Analysis [ESP69]

Course highlights

EC points


Start date

5 August 2024

End date

9 August 2024

Course days

Monday to Friday (5 full days)

Course time

From 8:45 till 16:00 CEST


Dr. Linda Valeri

Course fee

€ 1250






Knowledge of implementation and interpretation of linear and logistic regression is required.


  • Advanced Statistics
  • Biostatistics
  • Methodology
  • Epidemiology
  • Public Health

Course Materials

Digitally, download instructions will be sent before the start of the course, by e-mail.

R will be used during the course.

Recommended book:

VanderWeele, T.J. (2015). Explanation in Causal Inference: Methods for Mediation and Interaction.

New York: Oxford University Press. ISBN 9780199325870.

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Itai Magodoro


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Detailed information about this course:



Faculty: Linda Valeri, PhD

The course covers recent developments in causal mediation analysis and provides practical tools to implement these techniques. Mediation analysis concerns assessing the mechanisms and pathways by which causal effects operate. The course covers the relationship between traditional methods for mediation in epidemiology and the social sciences and new methods in causal inference. For dichotomous and continuous outcomes, we discuss when the standard approaches to mediation analysis are valid. Using ideas from causal inference and natural direct and indirect effects, alternative mediation analysis techniques are described when the standard approaches do not work. The no-confounding assumptions needed for these techniques are described.

R packages to implement these techniques are covered and distributed to course participants and will be used in hands on exercises. SAS and Stata macros will be distributed. The use and implementation of sensitivity analysis techniques to assess the how sensitive conclusions are to violations of assumptions are covered. Discussion will be given to how such mediation analysis approaches can be extended to settings in which data come from a case-control study design. The methods will be illustrated by various applications.

The course will employ a combination of asynchronous learning, in live lecture and discussion, laboratory sessions and software demonstration. In a typical course day, mornings are devoted to in class discussion and laboratory sessions, afternoons are devoted to asynchronous learning. Slides are used to present material in lecture form. Extensive notes are available for students. A wide variety of examples from epidemiology and the social sciences will be used to illustrate the techniques and approaches. Ample time is given for discussion and questions. A variety of software packages will be discussed. Students will have worked exercises that they can complete on their own.

08:45 – 10:45 live class (via Zoom)
10:45 – 11:45 office hours*
13:00 - 16:00 asynchronous components and homework

* The instructor will be available from 10:45 to 11:45 to address students’ questions on course material, as well as queries regarding the application of mediation analysis approaches to specific research questions. Attendance to this office hours session is optional.


  • Understand when traditional methods for mediation fail
  • Learn the concepts about mediation from causal inference
  • Learn methods and sensitivity analysis techniques for mediation
  • Develop facility with use of software for mediation

Participant profile

Anyone who wants to learn about mediation analysis and is familiar with linear and logistic regression.