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An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach

Overview of attention for article published in BMC Pharmacology, June 2010
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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 (94th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
13 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
512 Dimensions

Readers on

mendeley
752 Mendeley
citeulike
3 CiteULike
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Title
An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach
Published in
BMC Pharmacology, June 2010
DOI 10.1186/1471-2210-10-6
Pubmed ID
Authors

Andrej-Nikolai Spiess, Natalie Neumeyer

Abstract

It is long known within the mathematical literature that the coefficient of determination R(2) is an inadequate measure for the goodness of fit in nonlinear models. Nevertheless, it is still frequently used within pharmacological and biochemical literature for the analysis and interpretation of nonlinear fitting to data.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 752 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 <1%
Brazil 4 <1%
Germany 3 <1%
Australia 3 <1%
France 2 <1%
Switzerland 2 <1%
Sweden 2 <1%
Japan 2 <1%
United Kingdom 2 <1%
Other 10 1%
Unknown 717 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 195 26%
Student > Master 132 18%
Researcher 117 16%
Student > Bachelor 54 7%
Student > Doctoral Student 44 6%
Other 124 16%
Unknown 86 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 158 21%
Engineering 95 13%
Environmental Science 60 8%
Biochemistry, Genetics and Molecular Biology 41 5%
Computer Science 29 4%
Other 215 29%
Unknown 154 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 February 2021.
All research outputs
#1,072,863
of 20,797,992 outputs
Outputs from BMC Pharmacology
#2
of 62 outputs
Outputs of similar age
#10,094
of 176,788 outputs
Outputs of similar age from BMC Pharmacology
#1
of 1 outputs
Altmetric has tracked 20,797,992 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 62 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 98% 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 176,788 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 94% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them