Title |
An R package for analyzing and modeling ranking data
|
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Published in |
BMC Medical Research Methodology, May 2013
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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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 2 | 1% |
Uganda | 1 | <1% |
Germany | 1 | <1% |
Sweden | 1 | <1% |
United Kingdom | 1 | <1% |
Unknown | 134 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 32 | 23% |
Student > Ph. D. Student | 27 | 19% |
Student > Master | 11 | 8% |
Student > Postgraduate | 8 | 6% |
Other | 8 | 6% |
Other | 27 | 19% |
Unknown | 27 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 18 | 13% |
Computer Science | 15 | 11% |
Psychology | 11 | 8% |
Social Sciences | 11 | 8% |
Medicine and Dentistry | 10 | 7% |
Other | 45 | 32% |
Unknown | 30 | 21% |