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To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice

Overview of attention for article published in Journal of the American Medical Informatics Association, May 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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9 X users

Readers on

mendeley
1 Mendeley
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Title
To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice
Published in
Journal of the American Medical Informatics Association, May 2024
DOI 10.1093/jamia/ocae098
Pubmed ID
Authors

Maxwell Salvatore, Ritoban Kundu, Xu Shi, Christopher R Friese, Seunggeun Lee, Lars G Fritsche, Alison M Mondul, David Hanauer, Celeste Leigh Pearce, Bhramar Mukherjee

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users 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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Medicine and Dentistry 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 25 May 2024.
All research outputs
#6,401,713
of 25,982,087 outputs
Outputs from Journal of the American Medical Informatics Association
#1,505
of 3,359 outputs
Outputs of similar age
#42,270
of 186,251 outputs
Outputs of similar age from Journal of the American Medical Informatics Association
#4
of 21 outputs
Altmetric has tracked 25,982,087 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,359 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has gotten more attention than average, scoring higher than 55% 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 186,251 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.