Advanced Network Meta-analysis:
Recent Developments in Bayesian NMA
Network meta-analysis (NMA) is a method that combines results from different studies within a network of evidence to obtain an estimate of the relative difference in treatment effect and is a standard statistical method used in health technology assessments (HTA). NMA methodology is an active area of research and new methods are continually being developed to address new problems or to extend existing models. 

Join us as our panel of experts discusses some of the recent developments in Bayesian NMA. 

You’ll learn: 

• How NMA has developed since the method was first published. 
• How these new developments have been used to answer problems such as sparse data, time-to-event data, treatment interaction effects, and how real-world evidence can be incorporated into an NMA.
• How these new methods have been received by the National Institute for Health Care and Excellence (NICE). 


Adrian Vickers, PhD Director, Data Analytics and Design Strategy 

Emma Hawe, MSc Senior Director, Data Analytics and Design Strategy

Jean-Gabriel Le Moine, MS Associate Director, Data Analytics and Design Strategy 
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