Causal Inference in Epidemiology: Concepts and Methods

Description:

Many observational studies aim to make causal inferences about effects of interventions or exposures on health outcomes. This course defines causation, describes how emulating a ‘target trial’ can clarify the research question and guide analysis choices, introduces methods to make causal inferences from observational data and explains the assumptions underpinning them, which can be encoded using directed acyclic graphs (DAGs). Learning is consolidated by interactive discussion-based and computer practical sessions. The course is taught by academics and researchers from the University of Bristol’s Department of Population Health Sciences, MRC Integrative Epidemiology Unit and NIHR Bristol Biomedical Research Centre who are experts in the field with extensive experience of developing and applying relevant methods. This is an advanced course. Familiarity with regression models including Cox models for time-to-event data and their implementation in statistical software (R or Stata) is essential.

This course aims to define causation in biomedical research, describe methods to make causal inferences in epidemiology and health services research, and demonstrate the practical application of these methods.

The course will cover:

1. potential (counterfactual) outcomes;
2. causal diagrams (DAGs);
3. confounding and methods to control for confounding (stratification, regression, propensity scores and inverse probability weighting);
4. selection and information biases;
5. inverse probability weighting to deal with informative censoring
6. target trials to define a causal question about health interventions
7. instrumental variable estimation;
8. intention-to-treat and per-protocol effects in randomized trials and observational studies;
9. time-varying confounding, marginal structural models and other g-methods;
10. sequential approaches to emulating a target trial using observational data;
11. avoiding bias caused by immortal time: the clone-censor-IP weight approach;
12. model selection for causal inference studies
13. study designs for causal inference; and
14. reporting and triangulating causal inference studies

Cost:

£1,250

Website and registration:

Register for this course

Region:

South West

Keywords:

Regression Methods, causation, causal inference

Related publications and presentations from our eprints archive:

Regression Methods

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