elochoice {EloChoice}

Elo-ratings for pairwise comparisons of visual stimuli

Description

Elo-ratings for pairwise comparisons of visual stimuli

Usage

elochoice(winner, loser, kval = 100, startvalue = 0, runs = 1, normprob = FALSE)
eloint(winner, loser, allids, kval, startvalues, runs)
elointnorm(winner, loser, allids, kval, startvalues, runs)

Arguments

winner

character, vector with the IDs of the winning (preferred) and losing (not preferred) stimuli

loser

character, vector with the IDs of the winning (preferred) and losing (not preferred) stimuli

kval

numeric, k-value, which determines the maximum number of points a stimulus' rating can change after a single rating event, by default 100

startvalue

numeric, start value around which ratings are centered, by default 0

runs

numeric, number of randomizations

normprob

logical, by default FALSE, which indicates that a logistic approach is taken for calculating winning probabilities (see Elo 1978). Alternatively (TRUE), such that winning probabilities are calculated from a normal distribution

startvalues

numeric, start value around which ratings are centered, by default 0

allids

internal, character of all stimulus IDs in the data set

Details

elochoice() is the workhorse function of the package, which wraps up all the calculations for obtaining Elo-ratings and the information for the reliability index

eloint() and elointnorm() are internal functions (which elochoice() makes use of) that do most of the calculations, but are usually not directly addressed by the user.

Value

an object of class elochoice, i.e. a list with the following items

ratmat

numeric matrix with final ratings for each stimulus, one row per randomization

decmat

logical matrix showing for each randomization (row) and each single rating event (column) whether or not there was an expectation for that trial, i.e. whether the two stimuli's ratings differed before the rating

upsmat

logical matrix showing for each randomization (row) and each single rating event (column) whether or not the outcome of a trial was in the direction of the expectation, i.e. whether or not the higher rated stimulus won

wgtmat

numeric matrix showing for each randomization (row) and each single rating event (column) the absolute difference in ratings before the rating event

misc

various information

ov

data set overview, i.e. in how many trials was a stimulus involved and how many trials did each stimulus win and lose

ias

character matrix, with the original sequence of rating events

Author(s)

Christof Neumann

References

Elo AE (1978). The rating of chess players, past and present. Arco, New York.

Clark AP, Howard KL, Woods AT, Penton-Voak IS, Neumann C (2018). “Why rate when you could compare? Using the 'EloChoice' package to assess pairwise comparisons of perceived physical strength.” PloS one, 13(1), e0190393. doi: 10.1371/journal.pone.0190393.

Examples

data(physical)
set.seed(123)
res <- elochoice(winner = physical$Winner, loser = physical$Loser, runs = 100)
summary(res)
ratings(res, show = NULL, drawplot = TRUE)