↓ Skip to main content

Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data

Overview of attention for article published in BMC Medical Research Methodology, September 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
35 Mendeley
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.
Title
Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data
Published in
BMC Medical Research Methodology, September 2014
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.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Student > Master 6 17%
Researcher 4 11%
Student > Bachelor 4 11%
Librarian 2 6%
Other 5 14%
Unknown 6 17%
Readers by discipline Count As %
Medicine and Dentistry 12 34%
Nursing and Health Professions 5 14%
Mathematics 4 11%
Economics, Econometrics and Finance 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 4 11%
Unknown 7 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 14 October 2014.
All research outputs
#8,695,459
of 16,479,073 outputs
Outputs from BMC Medical Research Methodology
#903
of 1,555 outputs
Outputs of similar age
#78,888
of 205,718 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 16,479,073 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,555 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 41st percentile – i.e., 41% 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 205,718 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 61% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them