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Research Department of Epidemiology and Public Health (G19)

 

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Research Department of Epidemiology and Public Health (G19)

Radiance

G19 RADIANCE Estimating Causal Effects

Description

This course will cover 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 cover settings where the exposure/intervention is time fixed and will also give an overview to the more general case when exposures/treatments are time-varying (and hence may be affected by time varying confounding). 

https://radiance.org.uk/courses/estimating-causal-effects

Attendee CategoryCost   
PhD Student Rate.£45.00[Read More]
Standard Rate.£90.00[Read More]
Radiance

G19 RADIANCE Machine Learning in Causal Effects

Description

This intermediate course offers a comprehensive understanding of the links between machine learning and traditional methods in causal inference. This course was designed for participants that are familiar with causal inference and the fundamentals of Machine Learning.

 

Key Topics Covered :

Potential Outcomes: Understand the concept of potential outcomes and how machine learning can be applied to estimate casual effcts in observational studies.

Matching and Instrumental Variables: Explore advanced methods such as matching and instrumental variables to address confounding variables and strengthen casual inference models.

Trees and Regularisations: Learn how decision trees and regularisation techniques can be intergrated into casual analysis, providing participants with tools to handle complex datasets and improve model performance.

https://radiance.org.uk/machine-learning-and-causal-effects/

Attendee CategoryCost   
PhD Student Rate.£45.00[Read More]
Standard Rate.£90.00[Read More]
Radiance

G19 RADIANCE Target Trial Emulation

Description

This course is for anyone wishing to understand how comparisons of the effectiveness of alternative therapies or interventions can be performed using real world data (RWD) when adopting the framework of target trial emulation (TTE).  

RWD are data on the everyday experiences of individuals that are collected through surveys, cohort studies, administrative and clinical.  These data are observational, as opposed to experimental. Because of this, using them to address causal questions such as those of comparative effectiveness raises many concerns and difficulties. In this course you will learn the main sources of bias affecting RWD, how TTE can address some of them.  Students will have the opportunity to discuss its application in group discussions and computer practicals (in Stata and R). We will devote time to demonstrate how to implement the data management as well as the analytical steps to estimate the intention-to-treatment and per-protocol effects of time-fixed and time-varying interventions. 

https://radiance.org.uk/courses/target-trial-emulation

Attendee CategoryCost   
PhD Student Rate.£45.00[Read More]
Standard Rate.£90.00[Read More]

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