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Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation

Overview of attention for article published in BMC Medical Research Methodology, October 2016
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2 X users

Citations

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57 Dimensions

Readers on

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110 Mendeley
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1 CiteULike
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Title
Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation
Published in
BMC Medical Research Methodology, October 2016
DOI 10.1186/s12874-016-0239-7
Pubmed ID
Authors

Simone Wahl, Anne-Laure Boulesteix, Astrid Zierer, Barbara Thorand, Mark A. van de Wiel

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 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 17%
Researcher 18 16%
Student > Master 14 13%
Student > Bachelor 7 6%
Other 7 6%
Other 20 18%
Unknown 25 23%
Readers by discipline Count As %
Medicine and Dentistry 28 25%
Nursing and Health Professions 9 8%
Computer Science 7 6%
Agricultural and Biological Sciences 5 5%
Psychology 5 5%
Other 22 20%
Unknown 34 31%
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 30 November 2020.
All research outputs
#15,651,328
of 23,262,131 outputs
Outputs from BMC Medical Research Methodology
#1,545
of 2,056 outputs
Outputs of similar age
#198,616
of 315,270 outputs
Outputs of similar age from BMC Medical Research Methodology
#33
of 44 outputs
Altmetric has tracked 23,262,131 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,056 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 16th percentile – i.e., 16% 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 315,270 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.