% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api-simulation.R
\name{plot.mfrm_design_evaluation}
\alias{plot.mfrm_design_evaluation}
\title{Plot a design-simulation study}
\usage{
\method{plot}{mfrm_design_evaluation}(
  x,
  facet = c("Rater", "Criterion", "Person"),
  metric = c("separation", "reliability", "infit", "outfit", "misfitrate",
    "severityrmse", "severitybias", "convergencerate", "elapsedsec", "mincategorycount",
    "designdensity", "plannedmissingrate", "linkpersons", "linkfraction", "linkraters",
    "mincommonpersons", "zerocommonpairs", "pairsshorttarget"),
  x_var = c("n_person", "n_rater", "n_criterion", "raters_per_person"),
  group_var = NULL,
  draw = TRUE,
  ...
)
}
\arguments{
\item{x}{Output from \code{\link[=evaluate_mfrm_design]{evaluate_mfrm_design()}}.}

\item{facet}{Facet to visualize.}

\item{metric}{Metric to plot.}

\item{x_var}{Design variable used on the x-axis. When \code{x} was generated from
a \code{sim_spec} with custom public facet names, the corresponding aliases
(for example \code{n_judge}, \code{n_task}, \code{judge_per_person}) are also accepted.
Role keywords (\code{person}, \code{rater}, \code{criterion}, \code{assignment}) are accepted
as an abstraction over the current two-facet schema.}

\item{group_var}{Optional design variable used for separate lines. The same
alias rules as \code{x_var} apply.}

\item{draw}{If \code{TRUE}, draw with base graphics; otherwise return plotting data.}

\item{...}{Reserved for generic compatibility.}
}
\value{
If \code{draw = TRUE}, invisibly returns a plotting-data list. If
\code{draw = FALSE}, returns that list directly. The returned list includes
resolved canonical variables (\code{x_var}, \code{group_var}) together with public
labels (\code{x_label}, \code{group_label}), \code{design_variable_aliases}, and
\code{design_descriptor}, plus \code{planning_scope}, \code{planning_constraints}, and
\code{planning_schema}.
}
\description{
Plot a design-simulation study
}
\details{
This method is designed for quick design-planning scans rather than polished
publication graphics.

Useful first plots are:
\itemize{
\item rater \code{metric = "separation"} against \code{x_var = "n_person"}
\item criterion \code{metric = "severityrmse"} against \code{x_var = "n_person"}
when you want aligned recovery error rather than raw location shifts
\item rater \code{metric = "convergencerate"} against \code{x_var = "raters_per_person"}
\item sparse linked \code{metric = "plannedmissingrate"}, \code{"mincommonpersons"},
\code{"zerocommonpairs"}, or \code{"pairsshorttarget"} to review planned
missingness and rater-pair linkage separately from recovery metrics
}
}
\examples{
\donttest{
sim_eval <- suppressWarnings(evaluate_mfrm_design(
  n_person = c(8, 12),
  n_rater = 2,
  n_criterion = 2,
  raters_per_person = 1,
  reps = 1,
  maxit = 30,
  seed = 123
))
p <- plot(sim_eval, facet = "Rater", metric = "separation", x_var = "n_person", draw = FALSE)
c(p$facet, p$x_var)
}
}
\seealso{
\code{\link[=evaluate_mfrm_design]{evaluate_mfrm_design()}}, \link{summary.mfrm_design_evaluation}
}
