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Extending the sufficient component cause model to describe the Stable Unit Treatment Value Assumption (SUTVA)

Overview of attention for article published in Epidemiologic Perspectives & Innovations, April 2012
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1 X user

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63 Mendeley
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1 CiteULike
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Title
Extending the sufficient component cause model to describe the Stable Unit Treatment Value Assumption (SUTVA)
Published in
Epidemiologic Perspectives & Innovations, April 2012
DOI 10.1186/1742-5573-9-3
Pubmed ID
Authors

Sharon Schwartz, Nicolle M Gatto, Ulka B Campbell

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
United Kingdom 1 2%
Germany 1 2%
Belgium 1 2%
Unknown 56 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 27%
Student > Master 9 14%
Researcher 8 13%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Other 10 16%
Unknown 13 21%
Readers by discipline Count As %
Medicine and Dentistry 12 19%
Social Sciences 10 16%
Mathematics 7 11%
Decision Sciences 5 8%
Economics, Econometrics and Finance 3 5%
Other 12 19%
Unknown 14 22%
Attention Score in Context

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 27 September 2018.
All research outputs
#22,034,863
of 24,583,586 outputs
Outputs from Epidemiologic Perspectives & Innovations
#35
of 35 outputs
Outputs of similar age
#149,894
of 165,067 outputs
Outputs of similar age from Epidemiologic Perspectives & Innovations
#2
of 2 outputs
Altmetric has tracked 24,583,586 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 35 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one scored the same or higher as 0 of them.
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 165,067 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.