Graphical tools for network meta-analysis in STATA.

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 f...

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Main Authors: Anna Chaimani, Julian P T Higgins, Dimitris Mavridis, Panagiota Spyridonos, Georgia Salanti
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3789683?pdf=render
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spelling doaj-12dcc3ea76134e2bb5e83ecb2b442eb42020-11-25T02:25:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01810e7665410.1371/journal.pone.0076654Graphical tools for network meta-analysis in STATA.Anna ChaimaniJulian P T HigginsDimitris MavridisPanagiota SpyridonosGeorgia SalantiNetwork 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.http://europepmc.org/articles/PMC3789683?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Anna Chaimani
Julian P T Higgins
Dimitris Mavridis
Panagiota Spyridonos
Georgia Salanti
spellingShingle Anna Chaimani
Julian P T Higgins
Dimitris Mavridis
Panagiota Spyridonos
Georgia Salanti
Graphical tools for network meta-analysis in STATA.
PLoS ONE
author_facet Anna Chaimani
Julian P T Higgins
Dimitris Mavridis
Panagiota Spyridonos
Georgia Salanti
author_sort Anna Chaimani
title Graphical tools for network meta-analysis in STATA.
title_short Graphical tools for network meta-analysis in STATA.
title_full Graphical tools for network meta-analysis in STATA.
title_fullStr Graphical tools for network meta-analysis in STATA.
title_full_unstemmed Graphical tools for network meta-analysis in STATA.
title_sort graphical tools for network meta-analysis in stata.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description 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.
url http://europepmc.org/articles/PMC3789683?pdf=render
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AT panagiotaspyridonos graphicaltoolsfornetworkmetaanalysisinstata
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