MF9570 – New statistical methods for causal inference
Schedule, syllabus and examination date
New statistical models for causal inference are increasingly being used in epidemiology, clinical research and other fields. This course gives an introduction to some basic concepts and ideas in this area.
Important concepts and methods that will be covered are:
- Directed acyclic graphs (DAGs),
- counterfactual causality,
- marginal structural models,
- direct and indirect effects,
- selection bias.
These methods were developed over the last couple of decades, mainly by researchers at Harvard University (James M. Robins, Donald B. Rubin). The methods are part of a new approach to understanding how statistical analysis can form the basis of causal inference.
In epidemiology and clinical research much knowledge about the causal effects of treatments and risk factors comes from statistical studies. The new tools give a much more precise way of approaching these issues.
There is a great international interest in these approaches and we wish to make Norwegian reserachers acquainted with these developments.
- Understand basic ideas of causal inference
- Have knowledge of the most important methods
- Be able to apply analysis of causal DAGs
- Understand counterfactual analysis and time-dependent confounding
- Understand the challenges and possibilities of mediation analysis
PhD candidates at UiO will get first priority to the course. Maximum number of participants is 50.
How to apply:
- PhD candidates admitted to a PhD programme at UiO apply in StudentWeb
- Applicants who are not admitted to a PhD programme at UiO must apply for a right to study PhD courses in medicine and health sciences in SøknadsWeb before they can apply for this course. External applicants should apply for a right to study minimum 3 weeks before the course application deadline. See information about how to apply for at right to study and how to apply for PhD courses here: How external applicants can apply for elective PhD courses in medicine and health sciences.
Reply to course application:
Formal prerequisite knowledge
Recommended previous knowledge
The course presupposes a thorough understanding of methodology as used in epidemiology and related fields. It is an advantage to have knowledge of logistic regression or Cox regression
The course is organized as full day teaching over 4 days, including lectures, exercises and discussions.
You have to participate in at least 80 % of the teaching to be allowed to take the exam. Attendance will be registered.
A take-home exam will be given at the end of the course.
Submit assignments in Inspera
You submit your assignment in the digital examination system Inspera. Read about how to submit your assignment.
Use of sources and citation
Grades are awarded on a pass/fail scale. Read more about the grading system.
Explanations and appeals
Resit an examination
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.