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Correction to: Coincidence analysis: a new method for causal inference in implementation science

Overview of attention for article published in Implementation Science, January 2021
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1 tweeter

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4 Mendeley
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Title
Correction to: Coincidence analysis: a new method for causal inference in implementation science
Published in
Implementation Science, January 2021
DOI 10.1186/s13012-020-01079-8
Authors

Rebecca Garr Whitaker, Nina Sperber, Michael Baumgartner, Alrik Thiem, Deborah Cragun, Laura Damschroder, Edward J. Miech, Alecia Slade, Sarah Birken

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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 50%
Student > Doctoral Student 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 25%
Psychology 1 25%
Medicine and Dentistry 1 25%
Engineering 1 25%

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 13 January 2021.
All research outputs
#17,728,622
of 19,998,134 outputs
Outputs from Implementation Science
#1,622
of 1,650 outputs
Outputs of similar age
#395,791
of 471,158 outputs
Outputs of similar age from Implementation Science
#102
of 102 outputs
Altmetric has tracked 19,998,134 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 1,650 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one is in the 1st percentile – i.e., 1% 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 471,158 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 102 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.