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Systematic review of methods for individual patient data meta- analysis with binary outcomes

Overview of attention for article published in BMC Medical Research Methodology, June 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
67 Dimensions

Readers on

mendeley
88 Mendeley
citeulike
1 CiteULike
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Title
Systematic review of methods for individual patient data meta- analysis with binary outcomes
Published in
BMC Medical Research Methodology, June 2014
DOI 10.1186/1471-2288-14-79
Pubmed ID
Authors

Doneal Thomas, Sanyath Radji, Andrea Benedetti

Abstract

Meta-analyses (MA) based on individual patient data (IPD) are regarded as the gold standard for meta-analyses and are becoming increasingly common, having several advantages over meta-analyses of summary statistics. These analyses are being undertaken in an increasing diversity of settings, often having a binary outcome. In a previous systematic review of articles published between 1999-2001, the statistical approach was seldom reported in sufficient detail, and the outcome was binary in 32% of the studies considered. Here, we explore statistical methods used for IPD-MA of binary outcomes only, a decade later.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 2%
Malaysia 1 1%
Italy 1 1%
Finland 1 1%
United Kingdom 1 1%
New Zealand 1 1%
United States 1 1%
Unknown 80 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 25%
Student > Ph. D. Student 13 15%
Student > Master 13 15%
Student > Postgraduate 6 7%
Professor > Associate Professor 6 7%
Other 19 22%
Unknown 9 10%
Readers by discipline Count As %
Medicine and Dentistry 29 33%
Mathematics 10 11%
Agricultural and Biological Sciences 7 8%
Psychology 5 6%
Business, Management and Accounting 3 3%
Other 17 19%
Unknown 17 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 18 October 2021.
All research outputs
#1,787,741
of 20,830,231 outputs
Outputs from BMC Medical Research Methodology
#285
of 1,858 outputs
Outputs of similar age
#19,659
of 207,470 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 20,830,231 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,858 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 84% 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 207,470 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% 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