Erasmus Summer Programme Courses
Take a look at all the courses in the Erasmus Summer Programme, and find the course right for you.View all ESP courses
Causal Mediation Analysis [ESP69]
21 August 2023
25 August 2023
Monday to Friday (5 full days)
From 8:45 till 16:00 CEST
Dr. Linda Valeri
Erasmus MC, Rotterdam NL
Knowledge of implementation and interpretation of linear and logistic regression is required.
- Advanced Statistics
- Public Health
Digitally, download instructions will be sent before the start of the course, by e-mail.
STATA or R will be used during the course.
VanderWeele, T.J. (2015). Explanation in Causal Inference: Methods for Mediation and Interaction.
New York: Oxford University Press. ISBN 9780199325870.
Design your programme
Use our Programme Configurator to design and plan your own programme.Configurator
Apply for this course
Want to secure your seat in this course?Apply here
The professors - who are at the cutting edge in their respective fields - bring science to life!Read the full story
Detailed information about this course:
NOTE: COURSE TIMETABLE DEVIATES FROM STANDARD COURSE TIMES
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 and described as well. 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 class 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 - 11:45 live class
13:00 - 16:00 asynchronous components and homework
- 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
Anyone who wants to learn about mediation analysis and is familiar with linear and logistic regression.