G19 RADIANCE Causal Mediation AnalysisInfo Location Attendee Categories Contact More Info Event Information
DescriptionThis course is for anyone wishing to learn to perfom mediation analysis and learn about the difficulties in dealing with multiple mediators. Various approaches will be presented, the course will have 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 (in Stata or R). https://radiance.org.uk/courses/causal-mediation-analysis/
Event Location
Attendee CategoriesStandard Rate.
Additional ItemsContactFor queries in regards to this Course please contact the following :-
PLEASE ONLY CONTACT THE ONLINE STORE DIRECTLY IF YOU ARE EXPERIENCING PROBLEMS WITH YOUR DEBIT/CREDIT CARD PAYMENT, FOR ALL OTHER QUERIES RELATING TO THIS COURSE, INCLUDING CANCELLATIONS THESE SHOULD BE DIRECTED TO THE CONTACT DETAILS ABOVE.
More InformationLearning objectives -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
Course Structure There will be 2 on-line live lectures and 2 on-line live practical sessions either in Stata or R.
Timetable
Pre-requisite 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
Refund requests are accepted in full 14 days before the course. No refunds requested after that will be accepted. | |||||||||||||||||||
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