You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
The use of continuous data versus binary data in MTC models: A case study in rheumatoid arthritis
|
|---|---|
| Published in |
BMC Medical Research Methodology, November 2012
|
| DOI | 10.1186/1471-2288-12-167 |
| Pubmed ID | |
| Authors |
Susanne Schmitz, Roisin Adams, Cathal Walsh |
| Abstract |
Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. When sufficient head to head evidence is not available Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates. While models can be fit to a broad range of efficacy measures, this paper illustrates the advantages of using continuous outcome measures compared to binary outcome measures. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 2% |
| Unknown | 56 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 21% |
| Student > Master | 9 | 16% |
| Researcher | 7 | 12% |
| Professor | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Other | 9 | 16% |
| Unknown | 13 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 26% |
| Mathematics | 5 | 9% |
| Psychology | 4 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 7% |
| Social Sciences | 3 | 5% |
| Other | 10 | 18% |
| Unknown | 16 | 28% |
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 07 November 2012.
All research outputs
#18,320,524
of 22,685,926 outputs
Outputs from BMC Medical Research Methodology
#1,726
of 2,001 outputs
Outputs of similar age
#139,700
of 183,492 outputs
Outputs of similar age from BMC Medical Research Methodology
#25
of 28 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,001 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 6th percentile – i.e., 6% 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 183,492 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.