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Network-meta analysis made easy: detection of inconsistency using factorial analysis-of-variance models

Overview of attention for article published in BMC Medical Research Methodology, May 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

q&a
1 Q&A thread

Citations

dimensions_citation
35 Dimensions

Readers on

mendeley
36 Mendeley
citeulike
1 CiteULike
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Title
Network-meta analysis made easy: detection of inconsistency using factorial analysis-of-variance models
Published in
BMC Medical Research Methodology, May 2014
DOI 10.1186/1471-2288-14-61
Pubmed ID
Authors

Hans-Peter Piepho

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Singapore 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 33%
Researcher 6 17%
Student > Postgraduate 3 8%
Professor > Associate Professor 3 8%
Student > Bachelor 2 6%
Other 8 22%
Unknown 2 6%
Readers by discipline Count As %
Medicine and Dentistry 12 33%
Mathematics 6 17%
Agricultural and Biological Sciences 6 17%
Unspecified 1 3%
Nursing and Health Professions 1 3%
Other 6 17%
Unknown 4 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 16 March 2016.
All research outputs
#6,432,324
of 12,373,180 outputs
Outputs from BMC Medical Research Methodology
#577
of 1,095 outputs
Outputs of similar age
#100,991
of 270,352 outputs
Outputs of similar age from BMC Medical Research Methodology
#4
of 6 outputs
Altmetric has tracked 12,373,180 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,095 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 45th percentile – i.e., 45% 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 270,352 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.