Abstract
Ranking is one of the simple and efficient data collection techniques to understand individuals' perception and preferences for some items such as products, people, and species. Ranking data are frequently collected when individuals are asked to rank a set of items according to a certain preference criterion. Over the years, many statistical models and methods have been developed for analyzing ranking data. This paper will give a literature review of these models and methods and present the recent advances of the analysis of ranking data. Copyright © 2019 Wiley Periodicals, Inc.
| Original language | English |
|---|---|
| Article number | e1483 |
| Journal | Wiley Interdisciplinary Reviews: Computational Statistics |
| Volume | 11 |
| Issue number | 6 |
| Early online date | Aug 2019 |
| DOIs | |
| Publication status | Published - Nov 2019 |
Citation
Yu, P. L. H., Gu, J., & Xu, H. (2019). Analysis of ranking data. Wiley Interdisciplinary Reviews: Computational Statistics, 11(6). Retrieved from https://doi.org/10.1002/wics.1483Keywords
- Data visualization
- Probability models
- Ranking data
- Statistical inference