| Title |
A Bayesian hierarchical logistic regression model of multiple informant family health histories
|
|---|---|
| Published in |
BMC Medical Research Methodology, March 2019
|
| DOI | 10.1186/s12874-019-0700-5 |
| Pubmed ID | |
| Authors |
Jielu Lin, Melanie F. Myers, Laura M. Koehly, Christopher Steven Marcum |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 22% |
| Unspecified | 5 | 11% |
| Student > Master | 3 | 7% |
| Researcher | 2 | 4% |
| Student > Doctoral Student | 2 | 4% |
| Other | 4 | 9% |
| Unknown | 19 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 5 | 11% |
| Computer Science | 3 | 7% |
| Nursing and Health Professions | 3 | 7% |
| Medicine and Dentistry | 3 | 7% |
| Linguistics | 2 | 4% |
| Other | 7 | 16% |
| Unknown | 22 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 2019.
All research outputs
#4,113,122
of 23,133,982 outputs
Outputs from BMC Medical Research Methodology
#667
of 2,036 outputs
Outputs of similar age
#87,185
of 351,339 outputs
Outputs of similar age from BMC Medical Research Methodology
#37
of 60 outputs
Altmetric has tracked 23,133,982 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,036 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 67% 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 351,339 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.