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Quantitative summaries of treatment effect estimates obtained with network meta-analysis of survival curves to inform decision-making

Overview of attention for article published in BMC Medical Research Methodology, December 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Quantitative summaries of treatment effect estimates obtained with network meta-analysis of survival curves to inform decision-making
Published in
BMC Medical Research Methodology, December 2013
DOI 10.1186/1471-2288-13-147
Pubmed ID
Authors

Shannon Cope, Jeroen P Jansen

Abstract

Increasingly, network meta-analysis (NMA) of published survival data are based on parametric survival curves as opposed to reported hazard ratios to avoid relying on the proportional hazards assumption. If a Bayesian framework is used for the NMA, rank probabilities associated with the alternative treatments can be obtained, which directly support decision-making. In the context of survival analysis multiple treatment effect measures are available to inform the rank probabilities.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
France 1 4%
Unknown 25 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Other 5 19%
Student > Ph. D. Student 5 19%
Student > Doctoral Student 2 7%
Lecturer 2 7%
Other 5 19%
Unknown 2 7%
Readers by discipline Count As %
Medicine and Dentistry 15 56%
Mathematics 3 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Economics, Econometrics and Finance 1 4%
Agricultural and Biological Sciences 1 4%
Other 2 7%
Unknown 4 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 02 December 2013.
All research outputs
#5,853,240
of 22,733,113 outputs
Outputs from BMC Medical Research Methodology
#890
of 2,004 outputs
Outputs of similar age
#67,937
of 307,131 outputs
Outputs of similar age from BMC Medical Research Methodology
#9
of 27 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,004 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 55% of its peers.
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 307,131 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 77% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.