% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api-methods.R
\name{summary.mfrm_bias}
\alias{summary.mfrm_bias}
\title{Summarize an \code{mfrm_bias} object in a user-friendly format}
\usage{
\method{summary}{mfrm_bias}(object, digits = 3, top_n = 10, p_cut = 0.05, ...)
}
\arguments{
\item{object}{Output from \code{\link[=estimate_bias]{estimate_bias()}}.}

\item{digits}{Number of digits for printed numeric values.}

\item{top_n}{Number of strongest bias rows to keep.}

\item{p_cut}{Significance cutoff used for counting flagged rows.}

\item{...}{Reserved for generic compatibility.}
}
\value{
An object of class \code{summary.mfrm_bias} with:
\itemize{
\item \code{overview}: interaction facets/order, cell counts, and effect-size profile
\item \code{chi_sq}: fixed-effect chi-square block
\item \code{final_iteration}: end-of-iteration status row
\item \code{top_rows}: highest-\verb{|t|} interaction rows
\item \code{notes}: short interpretation notes
}
}
\description{
Summarize an \code{mfrm_bias} object in a user-friendly format
}
\details{
This method returns a compact interaction-bias summary:
\itemize{
\item interaction facets/order and analyzed cell counts
\item effect-size profile (\verb{|bias|} mean/max, significant cell count)
\item fixed-effect chi-square block
\item iteration-end convergence indicators
\item top rows ranked by absolute t
}
}
\section{Interpreting output}{

\itemize{
\item \code{overview}: interaction order, analyzed cells, and effect-size profile.
\item \code{chi_sq}: fixed-effect test block.
\item \code{final_iteration}: end-of-loop status from the bias routine.
\item \code{top_rows}: strongest bias contrasts by \verb{|t|}; bounded \code{GPCM}
summaries also retain the profile-likelihood review columns when present.
}
}

\section{Typical workflow}{

\enumerate{
\item Estimate interactions with \code{\link[=estimate_bias]{estimate_bias()}}.
\item Check \code{summary(bias)} for screen-positive and unstable cells.
\item Use \code{\link[=bias_interaction_report]{bias_interaction_report()}} or \code{\link[=plot_bias_interaction]{plot_bias_interaction()}} for details.
}
}

\examples{
toy <- load_mfrmr_data("example_bias")
toy <- toy[toy$Person \%in\% unique(toy$Person)[1:8], ]
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 30)
diag <- diagnose_mfrm(fit, residual_pca = "none")
bias <- estimate_bias(fit, diag, facet_a = "Rater", facet_b = "Criterion", max_iter = 1)
summary(bias)
}
\seealso{
\code{\link[=estimate_bias]{estimate_bias()}}, \code{\link[=bias_interaction_report]{bias_interaction_report()}}
}
