An online short course
This course aims to provide an introduction to the conduct, assumptions, strengths and limitations of Mendelian randomization, including the use of up-to-date methods for sensitivity analyses that explore likely violation of Mendelian randomization assumptions.
|Course date||Due to demand this standalone course will run twice:
17 - 19 March 2021
21 - 23 April 2021
|Course Organisers||Professor Debbie Lawlor & Dr Kaitlin Wade|
Please ensure you meet the following prerequisites before booking:
|Knowledge||Prior experience of using Mendelian randomization is not required, but participants should have an understanding of aetiological epidemiological principles, and ideally be working on causal population health questions.
Those intending to take this course should already understand epidemiological principles and have knowledge and skills in statistical analysis to the level of running, and correctly interpreting results from, multivariable regression analyses.
They must have experience in running such analyses efficiently in Stata and/or R as all practicals on the course will be offered in both Stata and R and the focus of these practicals will be on Mendelian randomization (not learning how to use the statistical packages).
Note: it is not necessary for those participating in the course to be able to use both Stata and R, but you must be able to use one of these.
|Software||Participants who would like to use Stata need to have installed Stata version 16* in advance of the course.
Those who would like to use R (latest version) need to have this downloaded onto their computer.
The operating system can be either Windows or Mac and participants should consider having a fast internet speed for synchronous/live sessions and for downloading data and scripts.
*Internal University of Bristol participants will be provided with access to Stata version 16 on the first day of the course.
This 3-day course will be online and consist of learning activities set by the tutor including lectures (synchronous and asynchronous), small group work, discussions, individual tasks, and computer practical activities. Directed and self-directed learning will include activities such as reading, accessing web-based supplementary materials, critical appraisal and completion of quizzes. All teaching will be conducted online using Blackboard.
By the end of the course, students will be able to:
- describe the principles and assumptions of instrumental variable analyses;
- discuss the properties of genetic variants that make them suitable to be used as instrumental variables;
- explain the strengths and limitations of one-sample and two-sample Mendelian randomization for addressing population health causal questions;
- conduct a (straightforward) one-sample and two-sample Mendelian randomization analysis;
- describe the concepts behind sensitivity analyses to test for potential violation of the key assumptions of Mendelian randomization;
- apply up-to-date sensitivity analyses in one- and two-sample Mendelian randomization analyses;
- critically appraise Mendelian randomization papers and analyses;
- identify the key features required in writing reproducible and transparent Mendelian randomization papers;
- design a Mendelian randomization study of an exposure/outcome pair.
Who the course is intended for
The course is intended for anyone who wants to be able to undertake Mendelian randomization analyses. It is an introductory to intermediate course. The course will not include any genetic epidemiology teaching, nor how to undertake a genome-wide association study. However, genetic epidemiology and the ability to complete a genome-wide association study are NOT a prerequisite for being able to understand this course. The course will not cover more complex Mendelian randomization methods such as two-step or network Mendelian randomization.
Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal of Epidemiology 2015; 512–525. doi: 10.1093/ije/dyv080.
Lawlor DA. Two-sample Mendelian randomization: opportunities and challenges. International Journal of Epidemiology 2016; 908–915. doi: 10.1093/ije/dyw127.
Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. American Journal of Clinical Nutrition 2016; 103: 965–78.
Online Course Bookings
Bookings are open for online courses running in 2021.
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We may need to make responsive changes to our courses at short notice in order to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).