An Introduction to Network Meta-Analysis
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September 8, 2022

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Open to all ISPOR Members and Non-members


Title: An Introduction to Network Meta-Analysis

Thursday, September 8, 2022
10:00AM EDT | 2:00PM UTC | 4:00PM CEST

 
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Description

The Statistical Methods in Health Economics  and Outcome Research Special Interest Group is pleased to present two webinars on Network Meta-Analysis (NMA). The first of two webinars will focus on the terms associated with network meta-analyses, how and why different comparisons are used, and the concepts, assumptions, and limitations associated with NMA. The first webinar is focused on an Introduction to NMA by Emma Hawe. The second will cover special topics in NMA by Sofia Dias. Both webinars will be moderated by Gian Luca Di Tanna.

Learning Objectives

The learning objectives and key goals for this webinar include:

• Understand terms such as direct and indirect comparisons, mixed-treatment comparisons, and network meta- analyses (NMA) and why they are used.
• Gain an overview of the high-level steps to conduct an NMA and some of the key outputs.
• Recognize the difference between fixed and random effects and Frequentist and Bayesian methods.
• Garner an overview of concepts, assumptions, and limitations of NMAs, such as: heterogeneity, inconsistency, bias.

Moderator:

Gian Luca Di Tanna, PhD, MPhil, MSc, AStat, CStat,
 Head (Australia), Biostatistics and Data Science Division, The George Institute for Global Health, Newtown, Australia
 

Speaker: 

Emma Hawe, MSc, Head of Data Analytics and Design Strategy, RTI-HS, Manchester, England, UK

 
Brought to you by: ISPOR Statistical Methods in HEOR Special Interest Group


Please note:
On the day of the scheduled webinar, the first 1000 registered participants will be accepted into the webinar. For those who are unable to attend, or would like to review the webinar at a later date, the full-length webinar recording will be made available at the ISPOR Educational Webinar Series webpage approximately 2 days after the scheduled Webinar.

Reservations are on a first-come, first-served basis.

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