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Categorisation of continuous covariates for stratified randomisation: How should we adjust?

Overview of attention for article published in Statistics in Medicine, March 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
52 X users

Readers on

mendeley
12 Mendeley
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Title
Categorisation of continuous covariates for stratified randomisation: How should we adjust?
Published in
Statistics in Medicine, March 2024
DOI 10.1002/sim.10060
Pubmed ID
Authors

Thomas R. Sullivan, Tim P. Morris, Brennan C. Kahan, Alana R. Cuthbert, Lisa N. Yelland

X Demographics

X Demographics

The data shown below were collected from the profiles of 52 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 17%
Student > Ph. D. Student 2 17%
Researcher 2 17%
Lecturer > Senior Lecturer 1 8%
Student > Bachelor 1 8%
Other 3 25%
Unknown 1 8%
Readers by discipline Count As %
Mathematics 4 33%
Medicine and Dentistry 3 25%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Unspecified 1 8%
Design 1 8%
Other 0 0%
Unknown 2 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 08 April 2024.
All research outputs
#1,417,431
of 25,754,670 outputs
Outputs from Statistics in Medicine
#92
of 4,126 outputs
Outputs of similar age
#17,588
of 288,443 outputs
Outputs of similar age from Statistics in Medicine
#1
of 30 outputs
Altmetric has tracked 25,754,670 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,126 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 288,443 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.