Paola Zaninotto, Bianca De Stavola, Ellie Iob
This introductory course is for anyone wishing to have an overview of main concepts of mediation analysis. Various approaches will be presented with an emphasis on comparing standard approaches with those from the causal inference framework. The course consists of a lecture followed by a computer practical exercise.
During the computer practical session students will be given a data set and a set of questions to answer 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
There will be 1 on-line live lecture and 1 on-line live practical session either in Stata or R.
Wednesday 15th November
Live computer practical session
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”.
They might also wish to read
-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
This is a UKRI funded project offering rigorous training in longitudinal data science. Please note that this training is NOT available to undergraduate or masters students.