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Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data

Overview of attention for article published in BMC Medical Research Methodology, December 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Readers on

mendeley
20 Mendeley
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Title
Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data
Published in
BMC Medical Research Methodology, December 2022
DOI 10.1186/s12874-022-01781-9
Pubmed ID
Authors

Xuejia Ke, Katherine Keenan, V. Anne Smith

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

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 15%
Student > Doctoral Student 2 10%
Researcher 2 10%
Student > Bachelor 2 10%
Unspecified 1 5%
Other 2 10%
Unknown 8 40%
Readers by discipline Count As %
Environmental Science 2 10%
Medicine and Dentistry 2 10%
Unspecified 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Computer Science 1 5%
Other 3 15%
Unknown 10 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 December 2022.
All research outputs
#13,800,705
of 23,392,375 outputs
Outputs from BMC Medical Research Methodology
#1,324
of 2,065 outputs
Outputs of similar age
#171,090
of 433,439 outputs
Outputs of similar age from BMC Medical Research Methodology
#28
of 59 outputs
Altmetric has tracked 23,392,375 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,065 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 33rd percentile – i.e., 33% 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 433,439 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 58% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.