The Library
Modelling rankings in R: the PlackettLuce package
Tools
Turner, Heather , van Etten, Jacob, Firth, David and Kosmidis, Ioannis (2020) Modelling rankings in R: the PlackettLuce package. Computational Statistics, 35 . pp. 1027-1057. doi:10.1007/s00180-020-00959-3 ISSN 0943-4062.
|
PDF
WRAP-modelling-rankings-in-R-the-Placket-package-Turner-2020.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (501Kb) | Preview |
|
PDF
1810.12068.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (330Kb) |
Official URL: http://dx.doi.org/10.1007/s00180-020-00959-3
Abstract
This paper presents the R package PlackettLuce, which implements a generalization of the Plackett-Luce model for rankings data. The generalization accommodates both ties (of arbitrary order) and partial rankings (complete rankings of subsets of items). By default, the implementation adds a set of pseudo-comparisons with a hypothetical item, ensuring that the underlying network of wins and losses between items is always strongly connected. In this way, the worth of each item always has a finite maximum likelihood estimate, with finite standard error. The use of pseudo-comparisons also has a regularization effect, shrinking the estimated parameters towards equal item worth. In addition to standard methods for model summary, PlackettLuce provides a method to compute quasi standard errors for the item parameters. This provides the basis for comparison intervals that do not change with the choice of identifiability constraint placed on the item parameters. Finally, the package provides a method for model-based partitioning using covariates whose values vary between rankings, enabling the identification of subgroups of judges or settings that have different item worths. The features of the package are demonstrated through application to classic and novel data sets.
Item Type: | Journal Article | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics |
|||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | |||||||||
Library of Congress Subject Headings (LCSH): | Axiom of choice, Correlation (Statistics) | |||||||||
Journal or Publication Title: | Computational Statistics | |||||||||
Publisher: | Springer | |||||||||
ISSN: | 0943-4062 | |||||||||
Official Date: | 12 February 2020 | |||||||||
Dates: |
|
|||||||||
Volume: | 35 | |||||||||
Page Range: | pp. 1027-1057 | |||||||||
DOI: | 10.1007/s00180-020-00959-3 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||
Copyright Holders: | Authors | |||||||||
Date of first compliant deposit: | 26 May 2020 | |||||||||
Date of first compliant Open Access: | 26 May 2020 | |||||||||
RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year