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Method for evaluating prediction models that apply the results of randomized trials to individual patients

Overview of attention for article published in Trials, June 2007
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
70 Dimensions

Readers on

mendeley
80 Mendeley
citeulike
2 CiteULike
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Title
Method for evaluating prediction models that apply the results of randomized trials to individual patients
Published in
Trials, June 2007
DOI 10.1186/1745-6215-8-14
Authors

Andrew J Vickers, Michael W Kattan, Daniel J Sargent

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 3%
Vietnam 1 1%
France 1 1%
Canada 1 1%
United States 1 1%
Unknown 74 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 25%
Researcher 17 21%
Professor > Associate Professor 7 9%
Professor 7 9%
Other 6 8%
Other 20 25%
Unknown 3 4%
Readers by discipline Count As %
Medicine and Dentistry 52 65%
Mathematics 8 10%
Computer Science 5 6%
Social Sciences 2 3%
Engineering 2 3%
Other 3 4%
Unknown 8 10%

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 22 July 2021.
All research outputs
#12,291,390
of 18,707,006 outputs
Outputs from Trials
#3,351
of 4,842 outputs
Outputs of similar age
#171,540
of 280,853 outputs
Outputs of similar age from Trials
#1
of 1 outputs
Altmetric has tracked 18,707,006 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,842 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 23rd percentile – i.e., 23% 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 280,853 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
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