Introduction to Network Meta-Analysis

An online short course

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.

Course date 16 - 20 May 2022
Course fee £550
Course structure Taught over 5 consecutive mornings, 9.30am - 1pm.
Course Organisers Professor Nicky Welton & Dr Deborah Caldwell


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.
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:

Course objectives

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;
  7. 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

  • 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.
  • 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. For details see here

Recommended reading

Dias S, Welton NJ, Sutton AJ, Ades AE. Evidence synthesis for decision making Parts 1 - 7 Medical Decision Making 2013 33:597-691

Caldwell D. M. (2014) An overview of conducting systematic reviews with network meta-analysis. Systematic Reviews 3: 109.

Caldwell DM, Welton NJ. Approaches for synthesising complex mental-health interventions in meta-analysis. Evidence Based Mental Health. 2016. 19:16-21.  doi: 10.1136/eb-2015-102275

Bookings for this course have now closed.

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General bookings for all available 2021/22 short courses are open.

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An absolutely fantastic course - the best one I've been to, a higher quality than most of the courses I remember as a PhD student.

Course feedback, December 2019
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