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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Visualising disease progression on multiple variables with vector plots and path plots
|
|---|---|
| Published in |
BMC Medical Research Methodology, May 2009
|
| DOI | 10.1186/1471-2288-9-32 |
| Pubmed ID | |
| Authors |
Stanley E Lazic, Sarah L Mason, Andrew W Michell, Roger A Barker |
| Abstract |
It is often desirable to observe how a disease progresses over time in individual patients, rather than graphing group averages; and since multiple outcomes are typically recorded on each patient, it would be advantageous to visualise disease progression on multiple variables simultaneously. |
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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 8% |
| United Kingdom | 2 | 5% |
| Unknown | 32 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 24% |
| Researcher | 9 | 24% |
| Student > Master | 5 | 14% |
| Student > Postgraduate | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 2 | 5% |
| Unknown | 6 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 24% |
| Mathematics | 4 | 11% |
| Computer Science | 4 | 11% |
| Agricultural and Biological Sciences | 3 | 8% |
| Psychology | 3 | 8% |
| Other | 7 | 19% |
| Unknown | 7 | 19% |
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 08 May 2014.
All research outputs
#15,300,431
of 22,755,127 outputs
Outputs from BMC Medical Research Methodology
#1,504
of 2,007 outputs
Outputs of similar age
#95,276
of 111,805 outputs
Outputs of similar age from BMC Medical Research Methodology
#7
of 10 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,007 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 16th percentile – i.e., 16% 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 111,805 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.