% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/diagnostics.R
\name{acs_reliability}
\alias{acs_reliability}
\title{Categorize ACS estimate reliability by CV thresholds.}
\usage{
acs_reliability(
  estimate,
  moe,
  conf = 0.9,
  thresholds = c(reliable = 0.12, caveat = 0.4)
)
}
\arguments{
\item{estimate}{Numeric estimate.}

\item{moe}{Numeric MOE.}

\item{conf}{Confidence level associated with \code{moe}.}

\item{thresholds}{Named numeric vector with \code{reliable} and \code{caveat} CV
thresholds. Defaults of 0.12 and 0.40 reflect commonly used applied
conventions (e.g., reliable below 12\% CV, unreliable above 40\% CV); these
are not a Census Bureau standard and should be adjusted to your domain,
agency guidance, or project-specific quality standard.}
}
\value{
Ordered factor with levels \code{reliable}, \code{caveat}, \code{unreliable}.
}
\description{
Categorize ACS estimate reliability by CV thresholds.
}
\examples{
acs_reliability(estimate = 1000, moe = 80)
acs_reliability(estimate = c(1000, 200, 50), moe = c(80, 60, 50))
}
