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Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers

Overview of attention for article published in BMC Medicine, July 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)

Mentioned by

policy
1 policy source
twitter
5 tweeters

Citations

dimensions_citation
305 Dimensions

Readers on

mendeley
206 Mendeley
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Title
Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers
Published in
BMC Medicine, July 2013
DOI 10.1186/1741-7015-11-159
Pubmed ID
Authors

Jeroen P Jansen, Huseyin Naci

Abstract

In the last decade, network meta-analysis of randomized controlled trials has been introduced as an extension of pairwise meta-analysis. The advantage of network meta-analysis over standard pairwise meta-analysis is that it facilitates indirect comparisons of multiple interventions that have not been studied in a head-to-head fashion. Although assumptions underlying pairwise meta-analyses are well understood, those concerning network meta-analyses are perceived to be more complex and prone to misinterpretation.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 206 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Australia 1 <1%
France 1 <1%
Saudi Arabia 1 <1%
Netherlands 1 <1%
Unknown 200 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 20%
Student > Ph. D. Student 31 15%
Student > Master 27 13%
Other 24 12%
Professor > Associate Professor 14 7%
Other 43 21%
Unknown 26 13%
Readers by discipline Count As %
Medicine and Dentistry 83 40%
Mathematics 16 8%
Psychology 14 7%
Pharmacology, Toxicology and Pharmaceutical Science 9 4%
Biochemistry, Genetics and Molecular Biology 8 4%
Other 38 18%
Unknown 38 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 February 2020.
All research outputs
#4,918,265
of 19,101,906 outputs
Outputs from BMC Medicine
#1,981
of 2,857 outputs
Outputs of similar age
#40,956
of 168,132 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 19,101,906 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,857 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 168,132 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them