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Meta-analysis, Simpson's paradox, and the number needed to treat

Overview of attention for article published in BMC Medical Research Methodology, January 2002
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Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
108 Dimensions

Readers on

mendeley
102 Mendeley
citeulike
1 CiteULike
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Title
Meta-analysis, Simpson's paradox, and the number needed to treat
Published in
BMC Medical Research Methodology, January 2002
DOI 10.1186/1471-2288-2-3
Pubmed ID
Authors

Douglas G Altman, Jonathan J Deeks

Abstract

There is debate concerning methods for calculating numbers needed to treat (NNT) from results of systematic reviews. We investigate the susceptibility to bias for alternative methods for calculating NNTs through illustrative examples and mathematical theory. Two competing methods have been recommended: one method involves calculating the NNT from meta-analytical estimates, the other by treating the data as if it all arose from a single trial. The 'treat-as-one-trial' method was found to be susceptible to bias when there were imbalances between groups within one or more trials in the meta-analysis (Simpson's paradox). Calculation of NNTs from meta-analytical estimates is not prone to the same bias. The method of calculating the NNT from a meta-analysis depends on the treatment effect used. When relative measures of treatment effect are used the estimates of NNTs can be tailored to the level of baseline risk. The treat-as-one-trial method of calculating numbers needed to treat should not be used as it is prone to bias. Analysts should always report the method they use to compute estimates to enable readers to judge whether it is appropriate.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 4%
France 2 2%
Spain 2 2%
India 1 <1%
Brazil 1 <1%
Austria 1 <1%
Canada 1 <1%
Netherlands 1 <1%
United States 1 <1%
Other 0 0%
Unknown 88 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 25%
Student > Ph. D. Student 19 19%
Professor > Associate Professor 11 11%
Professor 9 9%
Other 8 8%
Other 24 24%
Unknown 5 5%
Readers by discipline Count As %
Medicine and Dentistry 50 49%
Agricultural and Biological Sciences 10 10%
Mathematics 8 8%
Psychology 4 4%
Computer Science 3 3%
Other 18 18%
Unknown 9 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 November 2017.
All research outputs
#7,896,781
of 14,054,174 outputs
Outputs from BMC Medical Research Methodology
#812
of 1,291 outputs
Outputs of similar age
#126,417
of 267,676 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 14,054,174 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,291 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one is in the 35th percentile – i.e., 35% 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 267,676 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 50% 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