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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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 |
work_keys_str_mv |
AT annachaimani graphicaltoolsfornetworkmetaanalysisinstata AT julianpthiggins graphicaltoolsfornetworkmetaanalysisinstata AT dimitrismavridis graphicaltoolsfornetworkmetaanalysisinstata AT panagiotaspyridonos graphicaltoolsfornetworkmetaanalysisinstata AT georgiasalanti graphicaltoolsfornetworkmetaanalysisinstata |
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1724851156586332160 |