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A hierarchical Bayesian approach for handling missing classification data

Overview of attention for article published in Ecology and Evolution, March 2019
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

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33 Mendeley
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Title
A hierarchical Bayesian approach for handling missing classification data
Published in
Ecology and Evolution, March 2019
DOI 10.1002/ece3.4927
Pubmed ID
Authors

Alison C. Ketz, Therese L. Johnson, Mevin B. Hooten, N. Thompson Hobbs

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Researcher 5 15%
Student > Master 5 15%
Student > Bachelor 2 6%
Student > Doctoral Student 2 6%
Other 7 21%
Unknown 4 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 42%
Environmental Science 4 12%
Mathematics 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Immunology and Microbiology 2 6%
Other 4 12%
Unknown 5 15%
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 14 December 2021.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Ecology and Evolution
#7,183
of 8,478 outputs
Outputs of similar age
#284,175
of 367,878 outputs
Outputs of similar age from Ecology and Evolution
#241
of 279 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,478 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one is in the 8th percentile – i.e., 8% 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 367,878 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 279 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.