Plot facet-equivalence results

Usage

plot_facet_equivalence(
  x,
  diagnostics = NULL,
  facet = NULL,
  type = c("forest", "rope"),
  draw = TRUE,
  ...
)

Arguments

x: Output from analyze_facet_equivalence() or an eligible MML fit_mfrm() object. Legacy equivalence bundles must be recomputed.
diagnostics: Optional matching output from diagnose_mfrm() when x is an mfrm_fit object.
facet: Facet to analyze when x is an mfrm_fit object.
type: Plot type: "forest" (default) or "rope".
draw: If TRUE (default), draw the plot. If FALSE, return the prepared plotting data.
...: Reserved for compatibility; use the named plot controls.

Value

Invisibly, a ggplot object. Use plot_data() for the plotting data and inference/covariance basis. draw = FALSE returns the plot without printing.

Details

Fit inputs use the same eligibility checks as analyze_facet_equivalence(). Bundle inputs display the already calculated results. Both routes require the current inference and covariance basis, including when draw = FALSE.

Plot types

"forest" shows each level's deviation from the equally weighted facet mean, with covariance-aware deviation intervals and the practical region around zero. The raw marginal measure intervals remain in the data table.
"rope" shows the normal confidence-distribution mass within that region.

Interpreting output

Both plots describe grand-mean proximity. Colors in the forest plot indicate whether the deviation interval is inside, outside, or overlaps the practical region. Neither plot establishes pairwise equivalence or a Bayesian probability. Read the pairwise TOST results for pair-specific conclusions.

Typical workflow

Run analyze_facet_equivalence() with a prespecified practical bound.
Use type = "forest" to inspect deviations and their uncertainty.
Use type = "rope" for a descriptive proximity view.

Migration in 0.2.4

This renderer is internal. Use the corresponding plot() route in mfrmr_plot_migration; the former exported name is no longer available.

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("plot_facet_equivalence", run.dontrun = TRUE)
if (FALSE) { # \dontrun{
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "MML", quad_points = 31, maxit = 150)
eq <- analyze_facet_equivalence(fit, facet = "Rater")
p <- plot(eq, type = "facet_equivalence", view = "forest", draw = FALSE)
pdat <- plot_data(p)
c(pdat$facet, pdat$type)
} # }