This function can be used to detect exceptionally high or low scores in a vector.
exceptionalScore(x, prob = 0.025, both = TRUE, silent = FALSE,
quantileCorrection = 1e-04, quantileType = 8)Vector in which to detect exceptional scores.
Probability that a score is exceptionally positive or negative; i.e. scores
with a quartile lower than prob or higher than 1-prob are
considered exceptional (if both is TRUE, at least). So, note that a prob
of .025 means that if both=TRUE, the most exceptional 5% of the values is
marked as such.
Whether to consider values exceptional if they're below prob as well
as above 1-prob, or whether to only consider values exceptional if
they're below prob is prob is < .5, or above prob if
prob > .5.
Can be used to suppress messages.
By how much to correct the computed quantiles; this is used because when a distribution is very right-skewed, the lowest quantile is the lowest value, which is then also the mode; without subtracting a correction, almost all values would be marked as 'exceptional'.
The algorithm used to compute the quantiles; see quantile.
A logical vector, indicating for each value in the supplied vector whether it is exceptional.
Note that of course, by definition, prob of 2*prob percent of the
values is exceptional, so it is usually not a wise idea to remove scores based
on their 'exceptionalness'. Instead, use exceptionalScores,
which calls this function, to see how often participants answered
exceptionally, and remove them based on that.
# NOT RUN {
exceptionalScore(c(1,1,2,2,2,3,3,3,4,4,4,5,5,5,5,6,6,7,8,20), prob=.05);
# }
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