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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches
|
|---|---|
| Published in |
BMC Medical Research Methodology, December 2020
|
| DOI | 10.1186/s12874-020-01183-9 |
| Pubmed ID | |
| Authors |
Elizabeth Handorf, Yinuo Yin, Michael Slifker, Shannon Lynch |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 38% |
| Germany | 1 | 13% |
| Venezuela, Bolivarian Republic of | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Scientists | 2 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 17% |
| Student > Doctoral Student | 3 | 17% |
| Lecturer | 1 | 6% |
| Student > Master | 1 | 6% |
| Researcher | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 9 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 22% |
| Computer Science | 2 | 11% |
| Social Sciences | 2 | 11% |
| Nursing and Health Professions | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 8 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 13 January 2021.
All research outputs
#6,542,480
of 24,144,324 outputs
Outputs from BMC Medical Research Methodology
#979
of 2,144 outputs
Outputs of similar age
#154,726
of 515,145 outputs
Outputs of similar age from BMC Medical Research Methodology
#30
of 51 outputs
Altmetric has tracked 24,144,324 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,144 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 54% of its peers.
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 515,145 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 69% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.