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The use of continuous data versus binary data in MTC models: a case study in rheumatoid arthritis.

Date
2012
Abstract
Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. When sufficient head to head evidence is not available Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates. While models can be fit to a broad range of efficacy measures, this paper illustrates the advantages of using continuous outcome measures compared to binary outcome measures.
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Description
peer-reviewed
Publisher
BioMed Central Ltd.
Citation
BMC Medical Research Methodology;12: 167
Collections
Mathematics & Statistics
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Walsh_2012_binary.pdf
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Keywords
Bayesian mixed treatment comparison models, rheumatoid arthritis, anti-TNF agents
ULRR Identifiers
https://researchrepository.ul.ie/handle/10344/4931
 https://doi.org/10.34961/4208
Funding code
Funding Information
Sustainable Development Goals
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Type
Article
Rights
https://creativecommons.org/licenses/by-nc-sa/1.0/
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