% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api-dashboards.R
\name{plot_facet_quality_dashboard}
\alias{plot_facet_quality_dashboard}
\title{Plot a facet-quality dashboard}
\usage{
plot_facet_quality_dashboard(
  x,
  diagnostics = NULL,
  facet = NULL,
  bias_results = NULL,
  severity_warn = 1,
  misfit_warn = 1.5,
  central_tendency_max = 0.25,
  bias_count_warn = 1L,
  bias_abs_t_warn = 2,
  bias_abs_size_warn = 0.5,
  bias_p_max = 0.05,
  plot_type = c("severity", "flags"),
  top_n = 20,
  main = NULL,
  palette = NULL,
  label_angle = 45,
  draw = TRUE,
  ...
)
}
\arguments{
\item{x}{Output from \code{\link[=facet_quality_dashboard]{facet_quality_dashboard()}} or \code{\link[=fit_mfrm]{fit_mfrm()}}.}

\item{diagnostics}{Optional output from \code{\link[=diagnose_mfrm]{diagnose_mfrm()}} when \code{x} is a fit.}

\item{facet}{Optional facet name.}

\item{bias_results}{Optional bias bundle or list of bundles.}

\item{severity_warn}{Absolute estimate cutoff used to flag severity
outliers.}

\item{misfit_warn}{Mean-square cutoff used to flag misfit.}

\item{central_tendency_max}{Absolute estimate cutoff used to flag central
tendency.}

\item{bias_count_warn}{Minimum flagged-bias row count required to flag a
level.}

\item{bias_abs_t_warn}{Absolute \code{t} cutoff used when deriving bias-row
flags from a raw bias bundle.}

\item{bias_abs_size_warn}{Absolute bias-size cutoff used when deriving
bias-row flags from a raw bias bundle.}

\item{bias_p_max}{Probability cutoff used when deriving bias-row flags
from a raw bias bundle.}

\item{plot_type}{Plot type, \code{"severity"} or \code{"flags"}.}

\item{top_n}{Number of rows to keep in the plot data.}

\item{main}{Optional plot title.}

\item{palette}{Optional named color overrides.}

\item{label_angle}{Label angle hint for the \code{"flags"} plot.}

\item{draw}{If \code{TRUE}, draw with base graphics.}

\item{...}{Reserved for generic compatibility.}
}
\value{
A plotting-data object of class \code{mfrm_plot_data}.
}
\description{
Plot a facet-quality dashboard
}
\examples{
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 30)
diag <- diagnose_mfrm(fit, residual_pca = "none")
p <- plot_facet_quality_dashboard(fit, diagnostics = diag, draw = FALSE)
p$data$plot
}
\seealso{
\code{\link[=facet_quality_dashboard]{facet_quality_dashboard()}}, \code{\link[=summary.mfrm_facet_dashboard]{summary.mfrm_facet_dashboard()}}
}
