Causal Inference in Epidemiology: Recent Methodological Developments

Overview - Causal Inference in Epidemiology: Recent Methodological Developments

Causal inference is a central aim of many empirical investigations, and arguably most studies in the fields of medicine, epidemiology and public health. However, traditionally, the role of statistics is often relegated to quantifying the extent to which chance could explain the results, whilst concerns over systematic biases due to the non-ideal nature of the data are relegated to their qualitative discussion. The field known as causal inference has changed this state of affairs, setting causal questions within a coherent framework which facilitates explicit statement of all the assumptions underlying a given analysis, in many settings developing novel, flexible analysis methods, and allowing extensive exploration of potential biases.

This course will discuss the current state of the art with respect to these issues, while retaining a practical focus. The potential outcomes framework, causal diagrams, standardization, propensity scores, inverse probability weighting, instrumental variables, marginal structural models, causal mediation analysis and examples of sensitivity analysis will be discussed. Participants will acquire awareness of the common threads across these new methods and competence in applying them in simple settings.

Who should apply?

Participants will be expected to be numerate epidemiologists, or applied statisticians with an interest in epidemiology and clinical trials. An MSc in Epidemiology or Medical Statistics, or previous attendance to the Advanced Course in Epidemiological Analysis, would be an advantage.

Course objectives
Course objectives - Causal Inference in Epidemiology: Recent Methodological Developments

Course Content

The topics covered will be:

  • Causal language, estimands, and diagrams
  • Methods to deal with the bias introduced by measured and unmeasured confounders. These will include: standard regression methods, propensity score-based and instrumental variable methods
  • Marginal structural models for dealing with time-dependent confounding in longitudinal studies
  • Causal mediation analysis
  • Sensitivity analysis
  • Practical experience of the above methods in Stata

Course Certificate and Assessment

There will be no formal assessment. Participants will receive a Certificate of Attendance.

How to apply
How to apply - Causal Inference in Epidemiology: Recent Methodological Developments

Applying for this course

Register your interest to be notified when applications open.

Please read LSHTM's Admissions policies prior to submitting your application.

Short courses - visas, accommodation, disclaimer


The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team can provide supporting documentation if requested.


A list of hotels located in the vicinity of LSHTM, along with further resources for short term accommodation, can be found on our accommodation pages

Important information

Please note:

  • If you have been offered a place on the course you will not be able to register without bringing formal ID (Passport) and without having obtained the correct visa if required.
  • It is essential that you read the current visa requirements for short course students.
  • LSHTM may cancel courses two weeks before the first day of the course if numbers prove insufficient.  In those circumstances, course fees will be refunded.
  • LSHTM cannot accept responsibility for accommodation, travel and other losses incurred as a result of the course being cancelled.