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Malaria parasite clearance rate regression: an R software package for a Bayesian hierarchical regression model

Overview of attention for article published in Malaria Journal, January 2019
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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 (79th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
16 tweeters
facebook
1 Facebook page

Readers on

mendeley
3 Mendeley
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Title
Malaria parasite clearance rate regression: an R software package for a Bayesian hierarchical regression model
Published in
Malaria Journal, January 2019
DOI 10.1186/s12936-018-2631-8
Pubmed ID
Authors

Saeed Sharifi-Malvajerdi, Feiyu Zhu, Colin B. Fogarty, Michael P. Fay, Rick M. Fairhurst, Jennifer A. Flegg, Kasia Stepniewska, Dylan S. Small

Twitter Demographics

The data shown below were collected from the profiles of 16 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 1 33%
Unknown 2 67%
Readers by discipline Count As %
Mathematics 1 33%
Unknown 2 67%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 19 May 2019.
All research outputs
#1,903,772
of 14,547,858 outputs
Outputs from Malaria Journal
#536
of 4,177 outputs
Outputs of similar age
#75,894
of 375,122 outputs
Outputs of similar age from Malaria Journal
#56
of 476 outputs
Altmetric has tracked 14,547,858 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,177 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 86% 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 375,122 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 79% of its contemporaries.
We're also able to compare this research output to 476 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.