| 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. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Mexico | 1 | 25% |
| Colombia | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 101 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 | 93 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 22% |
| Student > Master | 15 | 15% |
| Student > Ph. D. Student | 14 | 14% |
| Professor > Associate Professor | 7 | 7% |
| Student > Doctoral Student | 6 | 6% |
| Other | 21 | 21% |
| Unknown | 16 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 31% |
| Mathematics | 10 | 10% |
| Agricultural and Biological Sciences | 7 | 7% |
| Psychology | 5 | 5% |
| Business, Management and Accounting | 3 | 3% |
| Other | 21 | 21% |
| Unknown | 24 | 24% |
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
#2,131,831
of 23,929,753 outputs
Outputs from BMC Medical Research Methodology
#312
of 2,117 outputs
Outputs of similar age
#21,764
of 231,456 outputs
Outputs of similar age from BMC Medical Research Methodology
#4
of 31 outputs
Altmetric has tracked 23,929,753 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,117 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 85% 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 231,456 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 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.