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Mendeley readers
Attention Score in Context
Title |
Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data
|
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Published in |
BMC Medical Research Methodology, September 2014
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DOI | 10.1186/1471-2288-14-105 |
Pubmed ID | |
Authors |
Pedro Saramago, Ling-Hsiang Chuang, Marta O Soares |
Abstract |
Network meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers. |
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 % |
---|---|---|
Unknown | 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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 1 | 2% |
Unknown | 40 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 20% |
Student > Master | 6 | 15% |
Researcher | 6 | 15% |
Student > Bachelor | 4 | 10% |
Other | 2 | 5% |
Other | 6 | 15% |
Unknown | 9 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 12 | 29% |
Mathematics | 5 | 12% |
Nursing and Health Professions | 5 | 12% |
Economics, Econometrics and Finance | 2 | 5% |
Computer Science | 1 | 2% |
Other | 6 | 15% |
Unknown | 10 | 24% |
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 19 September 2014.
All research outputs
#20,302,490
of 24,958,301 outputs
Outputs from BMC Medical Research Methodology
#1,919
of 2,225 outputs
Outputs of similar age
#177,390
of 244,775 outputs
Outputs of similar age from BMC Medical Research Methodology
#13
of 17 outputs
Altmetric has tracked 24,958,301 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,225 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. 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 244,775 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.