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\name{logit}
\alias{logit}
\title{Logit Transformation}
\description{
Compute the logit transformation of proportions or percentages.
}
\usage{
logit(p, percents, adjust)
}
\arguments{
\item{p}{numeric vector or array of proportions or percentages.}
\item{percents}{\code{TRUE} for percentages, \code{FALSE} for proportions. If the argument is missing and the largest value of \code{p} > 1, \code{percents} is set to \code{TRUE}, otherwise to \code{FALSE}.}
\item{adjust}{adjustment factor to avoid proportions of 0 or 1;
defaults to \code{0} if there are no such proportions in the data,
and to \code{.025} if there are.}
}
\details{
Computes the logit transformation logit \eqn{=\log [p/(1-p)]}{= log[p/(1 - p)]}
for the proportion \eqn{p}.
If \eqn{p=0}{p = 0} or \eqn{1}, then the logit
is undefined. \code{logit} can remap the proportions to the interval
\code{(adjust, 1 - adjust)} prior to the transformation. If it adjusts the data
automatically, \code{logit} will print a warning message.
}
\value{
a numeric vector or array of the same shape and size as \code{p}.
}
\references{
Fox, J. and Weisberg, S. (2019)
\emph{An R Companion to Applied Regression}, Third Edition, Sage.
}
\author{John Fox \email{jfox@mcmaster.ca} and Iain Proctor}
\seealso{\code{\link{probabilityAxis}}}
\examples{
save.opt <- options(digits=4)
logit(.1*0:10)
logit(.1*0:10, adjust=0)
logit(10*1:9, percents=TRUE)
options(save.opt)
}
\keyword{manip}
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