Description: Allows calculating global scores for characteristics of visual stimuli as assessed by human raters. Stimuli are presented as sequence of pairwise comparisons ('contests'), during each of which a rater expresses preference for one stimulus over the other (forced choice). The algorithm for calculating global scores is based on Elo rating, which updates individual scores after each single pairwise contest. Elo rating is widely used to rank chess players according to their performance. Its core feature is that dyadic contests with expected outcomes lead to smaller changes of participants' scores than outcomes that were unexpected. As such, Elo rating is an efficient tool to rate individual stimuli when a large number of such stimuli are paired against each other in the context of experiments where the goal is to rank stimuli according to some characteristic of interest. Clark et al (2018) <doi:10.1371/journal.pone.0190393> provide details.

Title: Optimized Elo Rating Method for Obtaining Dominance Ranks
person("Joseph", "Feldblum", email = "feldblum@umich.edu", role = c("aut", "cre")),
person("Steffen", "Foerster", email = "sf2041@gmail.com", role = c("aut")),
person("Mathias", "Franz", email = "m.franz@izw-berlin.de", role = c("aut")))
Description: Provides an implementation of the maximum likelihood methods for deriving
Elo scores as published in Foerster, Franz et al. (2016) <DOI:10.1038/srep35404>.
Imports: dplyr, reshape2, BAMMtools, tcltk, rlist, magrittr, lubridate,
Packaged: 2018-09-10 21:35:33 UTC; Joseph Feldblum

Imports: dplyr, reshape2, BAMMtools, magrittr, lubridate, rlang
Packaged: 2021-06-10 16:44:04 UTC; Joseph Feldblum

Title: Animal Dominance Hierarchies by Elo Rating
Description: Calculate Elo ratings as means to describe animal dominance hierarchies

Description: Provides functions to quantify animal dominance hierarchies. The major focus is on Elo rating and its ability to deal with temporal dynamics in dominance interaction sequences. For static data, David's score and de Vries' I&SI are also implemented. In addition, the package provides functions to assess transitivity, linearity and stability of dominance networks. See Neumann et al (2011) <doi:10.1016/j.anbehav.2011.07.016> for an introduction.
Depends: zoo, sna, network, R (>= 3.2.0)
Suggests: testthat, knitr, aniDom, rmarkdown
Packaged: 2019-12-04 23:06:29 UTC; christofneumann
Author: Christof Neumann [aut, cre] (<https://orcid.org/0000-0002-0236-1219>),