% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/es_from_PROP.R
\name{es_from_prop_single_group}
\alias{es_from_prop_single_group}
\title{Convert single-group proportion into an effect size measure}
\usage{
es_from_prop_single_group(prop, n_sample, prop_to_es = "raw", reverse_prop)
}
\arguments{
\item{prop}{proportion of cases in the single group (0-1)}

\item{n_sample}{total sample size}

\item{prop_to_es}{method used to compute the effect size from the proportion.
Must be \code{"raw"} (default), \code{"logit"}, or \code{"freeman_tukey"}.}

\item{reverse_prop}{a logical value indicating whether the direction of the proportion should be flipped.}
}
\value{
This function estimates a single-group proportion.

\tabular{ll}{
\code{natural effect size measure} \tab PROP\cr
\tab \cr
\code{converted effect size measure} \tab N/A\cr
\tab \cr
\code{required input data} \tab prop + n_sample\cr
\tab \cr
}

Note: when \code{prop_to_es = "logit"} or \code{"freeman_tukey"}, the returned
\code{prop}, \code{prop_se}, \code{prop_ci_lo} and \code{prop_ci_up} columns are
on the transformed (log-odds / Freeman-Tukey double-arcsine) scale, \strong{not}
the \verb{[0, 1]} proportion scale, and are not back-transformed. Only
\code{prop_to_es = "raw"} returns values on the proportion scale.
}
\description{
Convert single-group proportion into an effect size measure
}
\details{
This function computes an effect size from a single-group proportion.
\enumerate{
\item \strong{When \code{prop_to_es = "raw"}} (default), the proportion is used as the effect size
and its standard error is:
\deqn{prop\_se = \sqrt{\frac{prop \times (1 - prop)}{n}}}
\item \strong{When \code{prop_to_es = "logit"}}, the proportion is converted to a log odds:
\deqn{logit = \log\left(\frac{prop}{1 - prop}\right)}
\deqn{logit\_se = \sqrt{\frac{1}{n \times prop \times (1 - prop)}}}
\item \strong{When \code{prop_to_es = "freeman_tukey"}}, the Freeman-Tukey double arcsine
transformation is applied (Barendregt et al., 2013):
\deqn{FT = \frac{1}{2}\left[\arcsin\left(\sqrt{\frac{x}{n+1}}\right) + \arcsin\left(\sqrt{\frac{x+1}{n+1}}\right)\right]}
with \eqn{x = n \times prop}, and:
\deqn{FT\_se = \frac{1}{\sqrt{4n + 2}}}
}

When prop is equal to 0 or 1, a 0.5 correction is applied for the raw and logit methods:
\eqn{prop\_corrected = \frac{x + 0.5}{n + 1}}. For the raw method this shifts the
reported point estimate itself (a boundary proportion of exactly 0 or 1 is
returned as \eqn{(x + 0.5)/(n + 1)}, i.e. nudged toward the interior), matching
the convention of \code{metafor}'s \code{measure = "PR"}. The corrected
denominator \eqn{n + 1} also replaces \eqn{n} in the raw and logit standard
errors for these boundary rows (i.e.,
\eqn{\sqrt{p_c (1 - p_c) / (n + 1)}} and \eqn{\sqrt{1 / ((n + 1) \times p_c \times (1 - p_c))}}),
matching \code{metafor}'s \code{"PR"}/\code{"PLO"} convention throughout.

Proportions outside \eqn{[0, 1]} are set to NA with a warning (the affected
rows return NA, but do not abort the run).
}
\examples{
es_from_prop_single_group(prop = 0.30, n_sample = 100)
}
\references{
Barendregt, J. J., Doi, S. A., Lee, Y. Y., Norman, R. E., & Vos, T. (2013).
Meta-analysis of prevalence. Journal of Epidemiology and Community Health, 67(11), 974-978.

Miller, J. J. (1978). The inverse of the Freeman-Tukey double arcsine transformation.
The American Statistician, 32(4), 138-138. (Back-transformation left to the
user; not applied here: Freeman-Tukey results stay on the transformed scale.)
}
