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Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

Overview of attention for article published in BMC Bioinformatics, September 2010
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
228 Mendeley
citeulike
7 CiteULike
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Title
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms
Published in
BMC Bioinformatics, September 2010
DOI 10.1186/1471-2105-11-447
Pubmed ID
Authors

Yu Guo, Armin Graber, Robert N McBurney, Raji Balasubramanian

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 228 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 3%
United Kingdom 4 2%
Austria 1 <1%
Australia 1 <1%
Brazil 1 <1%
Germany 1 <1%
South Africa 1 <1%
Malaysia 1 <1%
Sweden 1 <1%
Other 1 <1%
Unknown 209 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 54 24%
Student > Ph. D. Student 45 20%
Student > Master 29 13%
Professor > Associate Professor 19 8%
Professor 18 8%
Other 42 18%
Unknown 21 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 25%
Medicine and Dentistry 24 11%
Computer Science 23 10%
Engineering 21 9%
Biochemistry, Genetics and Molecular Biology 18 8%
Other 50 22%
Unknown 35 15%

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 28 March 2022.
All research outputs
#13,789,697
of 22,100,013 outputs
Outputs from BMC Bioinformatics
#4,609
of 7,098 outputs
Outputs of similar age
#224,512
of 399,600 outputs
Outputs of similar age from BMC Bioinformatics
#321
of 484 outputs
Altmetric has tracked 22,100,013 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,098 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 399,600 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 484 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.