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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Advances in the meta-analysis of heterogeneous clinical trials I: The inverse variance heterogeneity model
|
|---|---|
| Published in |
Contemporary Clinical Trials, May 2015
|
| DOI | 10.1016/j.cct.2015.05.009 |
| Pubmed ID | |
| Authors |
Suhail A.R. Doi, Jan J. Barendregt, Shahjahan Khan, Lukman Thalib, Gail M. Williams |
| Abstract |
This article examines an improved alternative to the random effects (RE) model for meta-analysis of heterogeneous studies. It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure - the IVhet model. Extensive simulations confirm that this estimator retains a correct coverage probability and a lower observed variance than the RE model estimator, regardless of heterogeneity. When the proposed IVhet method is applied to the controversial meta-analysis of intravenous magnesium for the prevention of mortality after myocardial infarction, the pooled OR is 1.01 (95% CI 0.71 - 1.46) which favors the larger studies but also indicates more uncertainty around the point estimate. In comparison, under the RE model the pooled OR is 0.71 (95% CI 0.57 - 0.89) which, given the simulation results, probably reflects underestimation of the statistical error. Given the compelling evidence generated, we recommend that the IVhet model replace both the FE and RE models. To facilitate this, it has been implemented into a free meta-analysis software called MetaXL which can be downloaded from www.epigear.com. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 5 | 71% |
| Finland | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 43% |
| Members of the public | 3 | 43% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 145 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 17% |
| Student > Ph. D. Student | 16 | 11% |
| Student > Master | 13 | 9% |
| Student > Doctoral Student | 12 | 8% |
| Student > Bachelor | 12 | 8% |
| Other | 36 | 24% |
| Unknown | 33 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 34 | 23% |
| Nursing and Health Professions | 14 | 10% |
| Mathematics | 8 | 5% |
| Psychology | 6 | 4% |
| Social Sciences | 6 | 4% |
| Other | 29 | 20% |
| Unknown | 50 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 24 April 2024.
All research outputs
#1,537,445
of 25,374,647 outputs
Outputs from Contemporary Clinical Trials
#87
of 1,967 outputs
Outputs of similar age
#19,054
of 280,403 outputs
Outputs of similar age from Contemporary Clinical Trials
#2
of 31 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,967 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 95% 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 280,403 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 93% 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 93% of its contemporaries.