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TRAINING

DATA SCIENCE ADVANCED COURSES

Causal Mediation Analysis
27 – 28 NOVEMBER 2024

Paola Zaninotto, Bianca De Stavola, Giorgio Di Gessa

This course is for anyone wishing to have an overview of main concepts of mediation analysis and to appreciate the difficulties in dealing with multiple mediators. Various approaches will be presented with an emphasis on comparing standard approaches with those from the causal inference framework. The course consists of two lectures each followed by a computer practical exercise.

During the computer practical sessions a data set and a set of questions will be given to analyse using a statistical software (Stata or R), under the guidance of tutors.

-To understand when is appropriate to use mediation analysis

-Learn the key concepts of mediation analysis

-Learn to perform a mediation analysis using a real dataset

-Compare alternative approaches to deal with multiple mediators

There will be 2 on-line live lectures and 2 on-line live practical sessions either in Stata or R.

Date

Time

27 and 28/11/2024

9:30-13:00

Participants should attend “Estimating Causal effects” or have knowledge of Causal inference.

Ahead of the course Participants should watch the RADIANCE appetiser called “Causal questions”.

Recommended readings

-Chapter 1 of Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC, available here: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1268/2022/11/hernanrobins_WhatIf_13nov22.pdf

-VanderWeele, T.J. (2009). Mediation and mechanism. European Journal of Epidemiology, 24:217-224.

-VanderWeele, T.J. (2011). Controlled direct and mediated effects: definition, identification and bounds. Scandinavian Journal of Statistics,. 38,:P3, 551-563

– Zugna, D., Popovic, M., Fasanelli, F. et al. Applied causal inference methods for sequential mediators. BMC Med Res Methodol 22, 301 (2022). https://doi.org/10.1186/s12874-022-01764-w

£30 for PhD students and £60 for others