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Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Qstatistics

Overview of attention for article published in BMC Medical Research Methodology, April 2011
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Title
Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Qstatistics
Published in
BMC Medical Research Methodology, April 2011
DOI 10.1186/1471-2288-11-41
Pubmed ID
Authors

Jack Bowden, Jayne F Tierney, Andrew J Copas, Sarah Burdett

Abstract

Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 2 2%
Netherlands 1 <1%
Spain 1 <1%
Canada 1 <1%
Unknown 109 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 19%
Student > Ph. D. Student 17 15%
Student > Master 17 15%
Other 10 9%
Student > Bachelor 9 8%
Other 28 24%
Unknown 14 12%
Readers by discipline Count As %
Medicine and Dentistry 33 28%
Mathematics 12 10%
Business, Management and Accounting 7 6%
Psychology 7 6%
Social Sciences 7 6%
Other 26 22%
Unknown 25 21%

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 22 July 2013.
All research outputs
#17,252,485
of 21,347,367 outputs
Outputs from BMC Medical Research Methodology
#1,628
of 1,902 outputs
Outputs of similar age
#130,636
of 176,660 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
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