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#' exceptionalScore
#'
#' This function can be used to detect exceptionally high or low scores in a
#' vector.
#'
#' Note that of course, by definition, \code{prob} of \code{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
#' \code{\link{exceptionalScores}}, which calls this function, to see how often
#' participants answered exceptionally, and remove them based on that.
#'
#' @param x Vector in which to detect exceptional scores.
#' @param prob Probability that a score is exceptionally positive or negative;
#' i.e. scores with a quartile lower than \code{prob} or higher than
#' 1-\code{prob} are considered exceptional (if both is TRUE, at least). So,
#' note that a \code{prob} of .025 means that if both=TRUE, the most
#' exceptional 5\% of the values is marked as such.
#' @param both Whether to consider values exceptional if they're below
#' \code{prob} as well as above 1-\code{prob}, or whether to only consider
#' values exceptional if they're below \code{prob} is \code{prob} is < .5, or
#' above \code{prob} if \code{prob} > .5.
#' @param silent Can be used to suppress messages.
#' @param quantileCorrection 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'.
#' @param quantileType The algorithm used to compute the quantiles; see
#' \code{\link{quantile}}.
#' @return A logical vector, indicating for each value in the supplied vector
#' whether it is exceptional.
#' @author Gjalt-Jorn Peters
#'
#' Maintainer: Gjalt-Jorn Peters <gjalt-jorn@@userfriendlyscience.com>
#' @seealso \code{\link{quantile}}, \code{\link{exceptionalScores}}
#' @keywords univariate
#' @examples
#'
#' exceptionalScore(c(1,1,2,2,2,3,3,3,4,4,4,5,5,5,5,6,6,7,8,20), prob=.05);
#'
#' @export exceptionalScore
exceptionalScore <- function(x, prob=.025, both=TRUE, silent=FALSE,
quantileCorrection = .0001, quantileType = 8) {
belowLower <- x < (quantile(x, probs=min(c(prob, 1-prob)), na.rm=TRUE, type=quantileType) - quantileCorrection);
aboveUpper <- x > (quantile(x, probs=max(c(prob, 1-prob)), na.rm=TRUE, type=quantileType) + quantileCorrection);
if (both) {
return(belowLower | aboveUpper);
} else {
if (prob < .5) {
return(belowLower);
} else {
return(aboveUpper);
}
}
}
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