Estimating Causal Effects
06/11/2023 - 08/11/2023
University College London
Prof Bianca De Stavola, Dr Eduardo Fe, Prof Rhian Daniel, Ms. Andrea Aparicio Castro
Intermediate (some prior knowledge)
This course will introduce participants to the two main approaches to estimating causal effects from observational data: those based on the assumption of no unmeasured confounding and those that exploit the availability of instrumental variables. The course will focus on settings where the exposure/intervention is time fixed but will also give an introduction to the more general case when exposures/treatments are time-varying (and hence may be affected by time varying confounding).
To develop an understanding of the assumptions most commonly invoked in causal inference and some practical expertise in applying estimation methods that rely on them.
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Quantitative Data Handling and Data Analysis
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