↓ Skip to main content

Risk of using logistic regression to illustrate exposure-response relationship of infectious diseases

Overview of attention for article published in BMC Infectious Diseases, October 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
11 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Risk of using logistic regression to illustrate exposure-response relationship of infectious diseases
Published in
BMC Infectious Diseases, October 2014
DOI 10.1186/1471-2334-14-540
Pubmed ID
Authors

Jinma Ren, Zhen Ning, Carmen S Kirkness, Carl V Asche, Huaping Wang

Abstract

In most biological experiments, especially infectious disease, the exposure-response relationship is interrelated by a multitude of factors rather than many independent factors. Little is known about the suitability of ordinary, categorical exposures, and logarithmic transformation which have been presented in logistic regression models to assess the likelihood of an infectious disease as a function of a risk or exposure. This study aims to examine and compare the current approaches.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 9%
Sri Lanka 1 9%
Unknown 9 82%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 27%
Student > Ph. D. Student 3 27%
Researcher 2 18%
Student > Bachelor 1 9%
Professor > Associate Professor 1 9%
Other 0 0%
Unknown 1 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 18%
Medicine and Dentistry 2 18%
Computer Science 2 18%
Biochemistry, Genetics and Molecular Biology 1 9%
Nursing and Health Professions 1 9%
Other 2 18%
Unknown 1 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 24 December 2014.
All research outputs
#2,025,297
of 4,691,823 outputs
Outputs from BMC Infectious Diseases
#955
of 2,560 outputs
Outputs of similar age
#48,812
of 122,019 outputs
Outputs of similar age from BMC Infectious Diseases
#70
of 167 outputs
Altmetric has tracked 4,691,823 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 2,560 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 59% 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 122,019 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 167 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.