randompairs: generate random data of pairwise preference ratings
In EloChoice: Preference Rating for Visual Stimuli Based on Elo Ratings

Description Usage Arguments Details Value Author(s) Examples

generate random data of pairwise preference ratings

1	randompairs(nstim = 10, nint = 100, reverse = 0.1, skew = FALSE)

`nstim`	numeric, number of stimuli, must be less than 2,602
`nint`	numeric, number of paired ratings to be created
`reverse`	numeric, proportion of ratings that go against the default preference, see below for details
`skew`	logical, by default `FALSE`, see below for details

The default preference for a given pair is given by their alphanumerical order. E.g. A is preferred over M, and kf over kz. The reverse= argument specifies the proportion of ratings that go against this default order.

The number of appearances of a given stimulus in the data set is by default determined by uniform sampling of individual stimuli, i.e. all stimuli will roughly appear equally often in a data set. If a somewhat more realistic (i.e. unbalanced) distribution is desired, the argument skew=TRUE will achieve sampling based on a negative binomial distribution.

data.frame with winner and loser column. An additional column (index) serves as an index for the sequence in which the trials occurred.

Christof Neumann

# a relatively balanced data set
xdata <- randompairs(20, 500, skew=FALSE)
table(c(as.character(xdata$winner), as.character(xdata$loser)))
range(table(c(as.character(xdata$winner), as.character(xdata$loser))))

# and a less balanced data set
xdata <- randompairs(20, 500, skew=TRUE)
table(c(as.character(xdata$winner), as.character(xdata$loser)))
range(table(c(as.character(xdata$winner), as.character(xdata$loser))))

 b  c  d  e  f  g  h  i  j  k  n  p  s  t  u  v  w  x  y  z 
54 48 55 58 48 59 39 46 67 52 44 52 49 41 41 45 52 53 52 45 
[1] 39 67

 a  b  c  e  f  g  h  i  j  k  l  m  n  o  r  s  t  u  w  z 
50 28 34 74 77 59 35 44 12 51 18 41 51 17 64 24 88 69 65 99 
[1] 12 99