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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 17% |
| Portugal | 1 | 8% |
| United Kingdom | 1 | 8% |
| United States | 1 | 8% |
| Ireland | 1 | 8% |
| Italy | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 5 | 42% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 909 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 | 874 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 220 | 24% |
| Researcher | 141 | 16% |
| Student > Master | 138 | 15% |
| Student > Bachelor | 63 | 7% |
| Student > Doctoral Student | 53 | 6% |
| Other | 143 | 16% |
| Unknown | 151 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 170 | 19% |
| Engineering | 117 | 13% |
| Environmental Science | 69 | 8% |
| Biochemistry, Genetics and Molecular Biology | 50 | 6% |
| Computer Science | 36 | 4% |
| Other | 242 | 27% |
| Unknown | 225 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 01 September 2023.
All research outputs
#1,977,132
of 25,837,817 outputs
Outputs from BMC Pharmacology
#2
of 65 outputs
Outputs of similar age
#6,853
of 108,539 outputs
Outputs of similar age from BMC Pharmacology
#1
of 2 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 65 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 96% 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 108,539 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 92% of its contemporaries.
We're also able to compare this research output to 2 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