% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/assoc.R
\name{goodman_kruskal_tau}
\alias{goodman_kruskal_tau}
\title{Goodman-Kruskal's Tau}
\usage{
goodman_kruskal_tau(
  x,
  direction = c("row", "column"),
  detail = FALSE,
  conf_level = 0.95,
  digits = 3L,
  .include_se = FALSE
)
}
\arguments{
\item{x}{A contingency table (of class \code{table}).}

\item{direction}{Direction of prediction:
\code{"row"} (default, column predicts row) or
\code{"column"} (row predicts column).}

\item{detail}{Logical. If \code{FALSE} (default), return the estimate
as a numeric scalar. If \code{TRUE}, return a named numeric vector
including confidence interval and p-value.}

\item{conf_level}{A number between 0 and 1 giving the confidence
level (default \code{0.95}). Only used when \code{detail = TRUE}. Set
to \code{NULL} to omit the confidence interval.}

\item{digits}{Number of decimal places used when printing the
result (default \code{3}). Only affects the \code{detail = TRUE} output.}

\item{.include_se}{Internal parameter; do not use.}
}
\value{
Same structure as \code{\link[=cramer_v]{cramer_v()}}: a scalar when
\code{detail = FALSE}, a named vector when \code{detail = TRUE}.
The p-value tests H0: tau = 0 (Wald z-test).
}
\description{
\code{goodman_kruskal_tau()} computes Goodman-Kruskal's Tau, a
proportional reduction in error (PRE) measure for nominal
variables.
}
\details{
Unlike \code{\link[=lambda_gk]{lambda_gk()}}, Goodman-Kruskal's Tau uses all cell
frequencies rather than only the modal categories, making it
more sensitive to association patterns where lambda may be zero.
Standard error formulas follow the DescTools implementations
(Signorell et al., 2024); see \code{\link[=cramer_v]{cramer_v()}} for full references.
}
\examples{
tab <- table(sochealth$smoking, sochealth$education)
goodman_kruskal_tau(tab)
goodman_kruskal_tau(tab, direction = "column", detail = TRUE)

}
\seealso{
\code{\link[=lambda_gk]{lambda_gk()}}, \code{\link[=uncertainty_coef]{uncertainty_coef()}}, \code{\link[=assoc_measures]{assoc_measures()}}
}
