Causal Inference in Epidemiology: Recent Methodological Developments
London School of Hygiene and Tropical Medicine
Key Information
Campus location
Bloomsbury, United Kingdom
Languages
English
Study format
On-Campus
Duration
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Pace
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Tuition fees
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Application deadline
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Earliest start date
Aug 2023
Introduction
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 the awareness of the common threads across these new methods and competence in applying them in simple settings.