% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils-calc.R
\name{icc_tool_ci}
\alias{icc_tool_ci}
\title{Calculate ICC Confidence Intervals}
\usage{
icc_tool_ci(anova_result, icc_type, point_est, alpha = 0.05)
}
\arguments{
\item{anova_result}{List. Output from \code{icc_calc_anova}.}

\item{icc_type}{Character. ICC type code (matches icc_tool_point).}

\item{point_est}{Numeric. Point estimate from \code{icc_tool_point}.}

\item{alpha}{Numeric. Significance level, default 0.05 (95\% CI).}
}
\value{
A named list with CI results:
\describe{
  \item{ci_level}{Numeric. Confidence level (1 - alpha).}
  \item{ci_lower}{Numeric. Lower bound of CI (truncated to 0).}
  \item{ci_upper}{Numeric. Upper bound of CI (truncated to 1).}
  \item{df_corrected}{Numeric or NULL. Satterthwaite-corrected df (Type A only).}
}
}
\description{
Computes confidence intervals for all 10 ICC types using exact F-distribution
method from McGraw & Wong (1996) Table 7. Implements Satterthwaite degrees of
freedom correction for Type A ICC models (ICC(2,1), ICC(2,k) and their variants).
}
\references{
McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some
intraclass correlation coefficients. Psychological Methods, 1(1), 30-46.
}
\keyword{internal}
