Introduction to Network Meta-Analysis
This course aims to introduce network meta-analysis and show how the models can be estimated using R. Network meta-analysis (NMA) is a method that pools evidence from randomised controlled trials that compare two or more interventions, but where each trial may compare different interventions. NMA allows one to simultaneously estimate relative effectiveness for any pair of interventions in the evidence network.
I really enjoyed this short course! I rate 5/5 the effort, the tutors' willingness to explain thoroughly every technical detail and the organization of all sessions.
| Date | *Information on this page relates to the last run of the course and is for reference only.* |
|---|---|
| Fee | £550 |
| Format | Online |
| Structure | Taught over 5 consecutive mornings, 9.30am - 1pm. |
| Audience | Open to all applicants |
| Course Organisers | Professor Nicky Welton & Dr Deborah Caldwell |
Full course details
Course format
This online course will be taught over 5 consecutive mornings, 9.30am - 1pm.
Course objectives
By the end of the course participants should be able to:
- describe what indirect comparisons and network meta-analysis (NMA) are and why they are used;
- perform indirect comparisons using R;
- perform network meta-analysis using R, with continuous and dichotomous data;
- be aware of the assumptions made in NMA and use R to examine consistency;
- interpret different techniques used to present the results from NMA;
- appreciate how NMA can be used to combine evidence on complex interventions;
- critically appraise a paper that uses NMA.
Who the course is intended for
This course is designed for health services researchers, epidemiologists, statisticians, systematic reviewers and decision analysts.
Course outline
The course will cover:
- introduction to indirect comparisons, and combining direct and indirect evidence;
- introduction to network meta-analysis;
- performing NMA in R, including practicals;
- interpreting and presenting Results;
- assumptions made in network meta-analysis;
- assessing Inconsistency in NMA;
- systematic review to inform NMA;
- NMA for complex interventions;
- NMA for continuous outcomes; and
- critical appraisal of NMA, including group work.
Please note: The course gives an introduction to network meta-analysis using R. We also teach an alternative course on network meta-analysis using WINBUGS which has more focus on use in decision modelling.
IMPORTANT PREREQUISITES - please read before booking
Please ensure you meet the following prerequisites before booking:
| Knowledge | Experience of pairwise meta-analysis (to the level covered by the course Introduction to Systematic Reviews and Meta-analysis), understanding of statistical methods including logistic regression (to the level of the course Introduction to Linear and Logistic Regression Models), and basic experience with R. |
|---|---|
|
Software
|
You must have R (version 4.0.3 or higher) and RStudio (version 1.3.1093 or higher) installed in advance of the course. This course will use RStudio Desktop (Open Source version). This is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/
Go to R Installation Instructions for help getting set up.
|
This course is temporarily suspended.
Information on this page relates to the last run of the course and is for reference only.
University of Bristol staff and students may still access this course as a 'Materials Only' option.
Dates don't work? Just need a refresher?
Find out about the self-paced 'Materials Only' version of this course [available to University of Bristol staff and research postgraduates only].
Excellent course, one of the best I have done online. All went very smoothly, good pace and excellent content.