Estimating Causal Effects

Date:

06/11/2023 - 08/11/2023

Organised by:

University College London

Presenter:

Prof Bianca De Stavola, Dr Eduardo Fe, Prof Rhian Daniel, Ms. Andrea Aparicio Castro

Level:

Intermediate (some prior knowledge)

Contact:

radiance@ucl.ac.uk

Venue: Online

Description:

Course description

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).

Learning objectives

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.

Cost:

Free

Website and registration:

https://www.eventbrite.co.uk/e/estimating-causal-effects-tickets-486782809487

Region:

International

Keywords:

Quantitative Data Handling and Data Analysis

Related publications and presentations:

Quantitative Data Handling and Data Analysis

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