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Graphical Tools for Network Meta-Analysis in STATA

Overview of attention for article published in PLOS ONE, October 2013
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Title
Graphical Tools for Network Meta-Analysis in STATA
Published in
PLOS ONE, October 2013
DOI 10.1371/journal.pone.0076654
Pubmed ID
Authors

Anna Chaimani, Julian P. T. Higgins, Dimitris Mavridis, Panagiota Spyridonos, Georgia Salanti

Abstract

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 469 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 <1%
Korea, Republic of 1 <1%
Australia 1 <1%
Italy 1 <1%
Greece 1 <1%
United States 1 <1%
Unknown 460 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 92 20%
Student > Ph. D. Student 65 14%
Student > Master 55 12%
Other 36 8%
Student > Doctoral Student 24 5%
Other 113 24%
Unknown 84 18%
Readers by discipline Count As %
Medicine and Dentistry 183 39%
Mathematics 21 4%
Nursing and Health Professions 20 4%
Pharmacology, Toxicology and Pharmaceutical Science 18 4%
Social Sciences 14 3%
Other 92 20%
Unknown 121 26%