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An R package for analyzing and modeling ranking data

Overview of attention for article published in BMC Medical Research Methodology, May 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters
q&a
1 Q&A thread

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
130 Mendeley
citeulike
1 CiteULike
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Title
An R package for analyzing and modeling ranking data
Published in
BMC Medical Research Methodology, May 2013
DOI 10.1186/1471-2288-13-65
Pubmed ID
Authors

Paul H Lee, Philip LH Yu

Abstract

In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
Uganda 1 <1%
Germany 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Unknown 124 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 22%
Student > Ph. D. Student 27 21%
Student > Master 11 8%
Student > Postgraduate 8 6%
Other 8 6%
Other 27 21%
Unknown 21 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 13%
Computer Science 14 11%
Medicine and Dentistry 11 8%
Psychology 10 8%
Social Sciences 10 8%
Other 44 34%
Unknown 24 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 March 2015.
All research outputs
#3,456,068
of 12,373,180 outputs
Outputs from BMC Medical Research Methodology
#492
of 1,095 outputs
Outputs of similar age
#40,710
of 148,228 outputs
Outputs of similar age from BMC Medical Research Methodology
#6
of 11 outputs
Altmetric has tracked 12,373,180 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,095 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has gotten more attention than average, scoring higher than 54% 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 148,228 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 71% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.