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Two new approaches for the visualisation of models for network meta-analysis

Overview of attention for article published in BMC Medical Research Methodology, March 2019
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Mentioned by

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2 X users

Citations

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5 Dimensions

Readers on

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28 Mendeley
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Title
Two new approaches for the visualisation of models for network meta-analysis
Published in
BMC Medical Research Methodology, March 2019
DOI 10.1186/s12874-019-0689-9
Pubmed ID
Authors

Martin Law, Navid Alam, Areti Angeliki Veroniki, Yi Yu, Dan Jackson

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Student > Ph. D. Student 4 14%
Student > Master 4 14%
Professor 2 7%
Other 2 7%
Other 6 21%
Unknown 4 14%
Readers by discipline Count As %
Medicine and Dentistry 5 18%
Nursing and Health Professions 4 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Biochemistry, Genetics and Molecular Biology 2 7%
Arts and Humanities 1 4%
Other 7 25%
Unknown 7 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 27 March 2019.
All research outputs
#18,013,648
of 23,136,540 outputs
Outputs from BMC Medical Research Methodology
#1,701
of 2,037 outputs
Outputs of similar age
#269,822
of 380,317 outputs
Outputs of similar age from BMC Medical Research Methodology
#53
of 57 outputs
Altmetric has tracked 23,136,540 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,037 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 13th percentile – i.e., 13% 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 380,317 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.