| Title |
Visualizing inconsistency in network meta-analysis by independent path decomposition
|
|---|---|
| Published in |
BMC Medical Research Methodology, December 2014
|
| DOI | 10.1186/1471-2288-14-131 |
| Pubmed ID | |
| Authors |
Ulrike Krahn, Harald Binder, Jochem König |
| Abstract |
In network meta-analysis, several alternative treatments can be compared by pooling the evidence of all randomised comparisons made in different studies. Incorporated indirect conclusions require a consistent network of treatment effects. An assessment of this assumption and of the influence of deviations is fundamental for the validity evaluation. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 35 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 33% |
| Student > Ph. D. Student | 9 | 25% |
| Student > Master | 4 | 11% |
| Student > Doctoral Student | 2 | 6% |
| Professor | 2 | 6% |
| Other | 3 | 8% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 9 | 25% |
| Medicine and Dentistry | 8 | 22% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 11% |
| Social Sciences | 3 | 8% |
| Economics, Econometrics and Finance | 2 | 6% |
| Other | 6 | 17% |
| Unknown | 4 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 22 August 2023.
All research outputs
#6,848,630
of 23,943,619 outputs
Outputs from BMC Medical Research Methodology
#1,027
of 2,130 outputs
Outputs of similar age
#90,362
of 361,323 outputs
Outputs of similar age from BMC Medical Research Methodology
#17
of 25 outputs
Altmetric has tracked 23,943,619 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,130 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 50% 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 361,323 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 73% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.