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Facet reliability and separation snapshot bar plot

Source: R/api-plotting-secondary.R
plot_reliability_snapshot.Rd

Compact facet-level visual of the Wright & Masters (1982) separation, strata, and reliability indices that diagnose_mfrm() computes. Helpful as a single small figure for "are persons / raters / criteria distinguishable?" review. These are Rasch/FACETS-style separation indices on the fitted logit scale, not ICCs; use compute_facet_icc() for the complementary observed-score variance-share view.

Usage

plot_reliability_snapshot(
  fit,
  diagnostics = NULL,
  metric = c("reliability", "separation", "strata"),
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE
)

Arguments

fit

An mfrm_fit from fit_mfrm().

diagnostics

Optional diagnose_mfrm() output. Computed on demand when omitted.

metric

"reliability" (default), "separation", or "strata".

preset

Visual preset.

draw

If TRUE, draw with base graphics.

Value

An mfrm_plot_data whose data slot bundles a tidy Facet, Metric, Value data frame.

Session plot defaults

Set options(mfrmr.plot_preset = "publication") to choose a session default for plotting functions that expose the common preset argument. The supported values are "standard", "publication", "compact" and "monochrome". Precedence is an explicit call argument, then the session option, then "standard". For example, preset = "standard" overrides a session set to "monochrome". Explicit preset = NULL retains the earlier package-default behavior; it does not read the session option. Invalid session values cause an error only when that option is needed.

The category-curve, data-quality, fit-review, connectivity and network routes of plot() for report bundles use the same option through .... Plots without a common preset argument, including extended-model plots with their own palette controls, keep their own settings. This option selects a preset, not a universal theme or a guarantee that all renderers implement every appearance control identically.

New plot payloads retain the resolved preset for supported saved-data rendering. Converting an existing payload with as_ggplot() uses its saved appearance, even after the session option changes. A call that creates a new plot from a fit or statistical result uses the current default. For a reproducible script, supply preset explicitly or set the option in that script. Saving only the fitted model does not save a session option. No global ggplot theme is changed.

Restore previous settings with old <- options(mfrmr.plot_preset = "monochrome") followed by options(old). Use options(mfrmr.plot_preset = NULL) to remove the option. The preset changes appearance, not estimates, confidence levels or diagnostic thresholds.

See also

diagnose_mfrm(), mfrmr_visual_diagnostics

Examples

# \donttest{
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                 method = "JML", maxit = 300)
p <- plot_reliability_snapshot(fit, draw = FALSE)
p$data$table
#>       Facet      Metric     Value
#> 1     Rater reliability 0.9031009
#> 2    Person reliability 0.9005676
#> 3 Criterion reliability 0.8852451
# Look for (default `metric = "reliability"`):
# - >= 0.9 strong, 0.7-0.9 adequate, < 0.7 weak (Wright & Masters 1982).
# - The Person row is the operative reliability for ability scores.
# - Non-Person rows (Rater / Criterion) report the same index but
#   should be read as "are facet elements distinguishable?"; values
#   close to 1 mean facet means differ reliably from each other.
# }