Statistical Methods for Mediation Analysis
Mediation analysis examines what variables may lie on the causal pathway between an exposure and an outcome. Mediation models are useful for understanding aetiology, providing evidence to confirm and refute theory, and assessing the impact of intervening on a mediator when it is not possible to alter an exposure.
Dates | 24 - 25 June 2024* |
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Fee | £440 |
Format | Online |
Audience | Open to all applicants (prerequisites apply) |
*Advisory: previously advertised as 1-2 July
Course profile
This course aims to provide an understanding of the statistical principles behind, and the practical application of, mediation analyses in epidemiology.
Please click on the sections below for more information.
Structure
This 2 day course will take place online and consist of approximately 15 hours of teaching (including a mixture of live and pre-recorded lectures and live practical sessions).
The course will commence at 9am on the first day, and finish by 4.30pm on the final day.
Intended Learning Objectives
By the end of the course participants should:
- be aware of traditional and counterfactual approaches to mediation analysis and the assumptions underlying these methods;
- have a working knowledge of the Stata commands to run models for traditional and counterfactual approaches to mediation analysis;
- be aware of methods to incorporate multiple mediators and intermediate confounders; and
- have a working knowledge of the Stata commands to run models with multiple mediators or intermediate confounders.
Target audience
This course is intended for medical statisticians, and epidemiologists with a quantitative background and knowledge of linear and logistic regression.
Outline
The course will:
- review and critique traditional methods for mediation analyses;
- describe counterfactual-based approaches to mediation analysis;
- review traditional and counterfactual methods to incorporate multiple mediators; and
- introduce counterfactual methods to incorporate intermediate confounders.
Teaching staff
This course is taught by Dr Gemma Hammerton, Dr Ana Goncalves Soares, and Dr Jon Heron. All teaching staff have extensive experience in performing both traditional and counterfactual mediation analyses.
Prerequisites
To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:
Knowledge | Participants should have knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course. |
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Software |
You must have Stata* (version 14, 15, 16 ,17 or 18) installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are an employee of a university or another institution you may be able to get a short term free Evaluate license. If you are a student, Stata offer a short term free Student licence (one week). |
Bookings
Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.
Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms & conditions, which can be read in full here.
For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.
Course materials
Participants are granted access to our virtual learning platform (Blackboard) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.
To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.
All course participants retain access to the online learning materials and recordings for 3 months after the course.
University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials & Recordings' version of this course: Further information and bookings.
Testimonials
89% of attendees recommend this course*.
*Attendee feedback from 2022-2023.
Here is a sample of feedback from the last run of the course:
"Very good teaching, although online there were lots of opportunities to ask questions and interact with the lecturers who were very responsive to questions".
Course feedback, July 2023
"I think the virtual experience worked well, the padlet and Q&A sessions provided a lot of opportunity to ask questions and it is appreciated that the questions were answered as they came up. It was nice to have the option to dip in and out to either work on the practicals on our own or follow along".
Course feedback, July 2023
"I had prior knowledge of the concepts covered in this course, but what truly stood out was how the course helped me connect the dots and see the bigger picture. This is one of the most valuable benefits one can gain from an educational program".
Course feedback, July 2023
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Dates don't work? Just need a refresher?
Find out about the self-paced Materials & Recordings version of this course [UoB only].