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A progressive three-state model to estimate time to cancer: a likelihood-based approach

Overview of attention for article published in BMC Medical Research Methodology, June 2022
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Mentioned by

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1 X user

Citations

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2 Dimensions

Readers on

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5 Mendeley
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Title
A progressive three-state model to estimate time to cancer: a likelihood-based approach
Published in
BMC Medical Research Methodology, June 2022
DOI 10.1186/s12874-022-01645-2
Pubmed ID
Authors

Eddymurphy U. Akwiwu, Thomas Klausch, Henriette C. Jodal, Beatriz Carvalho, Magnus Løberg, Mette Kalager, Johannes Berkhof, Veerle M.H. Coupé

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor > Associate Professor 1 20%
Student > Doctoral Student 1 20%
Unknown 1 20%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 20%
Computer Science 1 20%
Economics, Econometrics and Finance 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%
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 28 June 2022.
All research outputs
#20,233,547
of 22,759,618 outputs
Outputs from BMC Medical Research Methodology
#1,872
of 2,009 outputs
Outputs of similar age
#350,673
of 438,799 outputs
Outputs of similar age from BMC Medical Research Methodology
#51
of 53 outputs
Altmetric has tracked 22,759,618 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 2,009 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. 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 438,799 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 53 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.