% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/reliability.R
\name{RMUreliability}
\alias{RMUreliability}
\title{Relative Measurement Uncertainty (RMU)}
\usage{
RMUreliability(input_draws, level = 0.95, verbose = FALSE)
}
\arguments{
\item{input_draws}{Numeric matrix or data.frame of draws. Rows are
subjects; columns are draws. Must have at least two columns; ideally many.}

\item{level}{Numeric in (0, 1). Width of the HDCI returned. Default \code{0.95}.}

\item{verbose}{Logical. Print summary information about the input. Default
\code{FALSE}.}
}
\value{
A 1-row data.frame with columns \code{rmu_estimate}, \code{hdci_lowerbound},
\code{hdci_upperbound}, plus the \code{.width}/\code{.point}/\code{.interval} metadata
columns added by \code{ggdist::mean_hdci()}.
}
\description{
Bayesian-style reliability estimate (Bignardi, Kievit & Bürkner, 2025)
computed from a matrix of posterior or plausible-value draws. The columns of
\code{input_draws} are split at random into two halves; reliability is the
Pearson correlation across persons of paired columns from the two halves,
summarised across pairs as a posterior mean with HDCI.
}
\details{
Adapted (with permission, GPL-2/3) from
\url{https://github.com/giac01/gbtoolbox/blob/main/R/reliability.R}.

The function silently returns 0 for any column pair where either side has
zero variance (the correlation is undefined there).

Requires the \code{ggdist} package (Suggests).
}
\references{
Bignardi, G., Kievit, R., & Bürkner, P. C. (2025). A general method for
estimating reliability using Bayesian Measurement Uncertainty. \emph{PsyArXiv}.
\doi{10.31234/osf.io/h54k8_v1}
}
\seealso{
\code{\link[=RMreliability]{RMreliability()}}
}
