This course is delivered online, via live sessions over 5 consecutive mornings, 9.30am - 1pm.

By the end of the course participants should be able to:

1. describe what indirect comparisons and network meta-analysis (NMA) are and why they are used;
2. perform indirect comparisons using R;
3. perform network meta-analysis using R, with continuous and dichotomous data;
4. be aware of the assumptions made in NMA and use R to examine consistency;
5. interpret different techniques used to present the results from NMA;
6. appreciate how NMA can be used to combine evidence on complex interventions; and
7. critically appraise a paper that uses NMA.

This course is designed for health services researchers, epidemiologists, statisticians, systematic reviewers, and decision analysts. It is an introductory to intermediate level course. No previous experience of network meta-analysis is assumed but the course materials assume a solid understanding and experience of meta-analysis and meta-regression.

This course will cover:

1. introduction to indirect comparisons, and combining direct and indirect evidence;
2. introduction to network meta-analysis;
3. performing NMA in R, including practicals;
4. interpreting and presenting Results;
5. assumptions made in network meta-analysis;
6. assessing Inconsistency in NMA;
7. systematic review to inform NMA;
8. NMA for complex interventions;
9. NMA for continuous outcomes; and
10. critical appraisal of NMA, including group work.

Please note: The course gives an introduction to network meta-analysis using R. We also teach an intermediate to advanced level course on network meta-analysis using WinBUGS which is more focused on NMA for decision modelling.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

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.

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. 

100% of attendees recommend this course*.
*Attendee feedback from 2024.

Here is a sample of feedback from the last run of the course:

“Nice mix of instructors with varied backgrounds. Optimal blend of theory and practicals. Very hands-on course - which is best way to learn. Nicely spread out over 5 days. Useful references and study material. Instructors very responsive to the queries that were posted” - Course feedback, March 2024.

“Different concepts were introduced in a logical order, allowing to gradually build up an understanding of NMA approach and contexts in which it is appropriate to use. The explanations and demonstrations were very clear and the lecturers and tutors managed to answer a lot of questions, both live and on the padlet, and provided useful resources for further questions that were beyond the scope of the course. The course provided a balanced view of NMA, highlighting both its advantages and limitations, and advising on good practices and cautioning against misuse of this method (a lot of attention was given to understanding and checking NMA assumptions). The content was easy to follow and assimilate thanks to a good balance of lectures and practicals” - Course feedback, March 2024.

“Well organized and executed course; the materials were excellent and I really enjoyed the practicals” - Course feedback, March 2024.

“The R code given and the way complex statistical concepts (such as MCMC and Bayesian priors) were explained was just right for the type and mix of students taking the course” - Course feedback, March 2024.

“The fact that this was a hand-on course made a huge difference. The pre-written R codes made it very useful for us to do the anlaysis on our own. I now have the confidence to conduct at least a simple NMA independently (of course with some support from an R expert if needed)” - Course feedback, March 2024.

“It was very practical with a lot of relevant exercises in R, which helped me understand better how the analysis works, as well as created useful resources for running the analyses myself in the future (like annotated script and guides for interpreting various outputs)” - Course feedback, March 2024.

“I enjoyed the lectures and demonstrations. It was great to have the padlets and chat for questions. The recordings were helpful to go over content that I didn't understand the first time” - Course feedback, March 2024.

“The whole course went well. I really enjoyed the "walk through" practical in R” - Course feedback, March 2024.

“Half day sessions were much easier to follow and digest. Very helpful course leaders/organisers” - Course feedback, March 2024.

“The lectures and the hands on practical was excellent. The timing was very good, half a day allowed me time to digest the materials! The coding along with tutors during practicals was phenomenal" - Course feedback, March 2024.