Person x facet-level standardized-residual matrix

Visualizes the person x element matrix of standardized residuals from diagnose_mfrm() as a heatmap. Complements plot_guttman_scalogram() (which shows raw responses) by exposing the residual structure directly: large positive cells show under-prediction, negative cells over-prediction.

Usage

plot_residual_matrix(
  fit,
  diagnostics = NULL,
  facet = "Rater",
  top_n_persons = 40L,
  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.

facet

Facet whose levels become the column axis (default "Rater").

top_n_persons

Cap on the number of rows. Defaults to 40 to keep the figure legible; persons are kept by largest absolute residual mean.

preset

Visual preset.

draw

If TRUE, draw with base graphics.

Value

An mfrm_plot_data whose data slot bundles the residual matrix (rows = Person, columns = facet level) and the long-form obs table.

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

plot_guttman_scalogram(), plot_unexpected(), 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_residual_matrix(fit, top_n_persons = 12, draw = FALSE)
dim(p$data$matrix)
#> [1] 12  4
# Look for: |residual| > 2 or > 3 crosses conventional two- or
#   three-standard-deviation review bands; these are heuristic screens,
#   not calibrated 5% or 1% tests (Wright & Linacre 1994). Repeated
#   high-magnitude cells at one facet level warrant pattern review but
#   do not by themselves establish scoring drift.
# }