Pairwise rater-agreement heatmap

Summarizes inter-rater agreement as a symmetric rater x rater heatmap. Cells are coloured by the chosen agreement metric: exact agreement proportion by default, or the Pearson-style Corr column from interrater_agreement_table() when metric = "correlation". The plot is a compact alternative to plot(x, type = "agreement")'s bar chart when the rater count exceeds ~6 pairs.

Usage

plot_rater_agreement_heatmap(
  fit,
  diagnostics = NULL,
  rater_facet = "Rater",
  metric = c("exact", "correlation"),
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE
)

Arguments

fit

An mfrm_fit.

diagnostics

Optional diagnose_mfrm() output; piped through to interrater_agreement_table() when supplied.

rater_facet

Name of the rater facet (default "Rater").

metric

Column to colour by: "exact" (default) or "correlation". Quadratic-weighted kappa is not currently computed by interrater_agreement_table() and is therefore not offered here.

preset

Visual preset.

draw

If TRUE, print the ggplot object.

Value

Invisibly, a ggplot object. plot_data(p) bundles the rater x rater matrix, raw pairwise rows, matching settings and palette. as_ggplot() preserves the selected metric, facet labels and unavailable cells, with a fixed 0–1 exact-agreement or -1–1 correlation scale. The "monochrome" preset applies to both renderers. Self comparisons are unavailable, not estimated perfect agreement. Save the plot payload with base::saveRDS() to convert it without recomputing diagnostics; interpretation notes remain in plot_data(p, "notes").

Session plot defaults

See mfrmr_visual_diagnostics for options(mfrmr.plot_preset), argument precedence, and appearance when saving or reusing a plot.

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.

See also

interrater_agreement_table() for the underlying numeric table; plot(x, type = "guttman") for a complementary person-by-element view of residual structure; diagnose_mfrm() for the diagnostics bundle the heatmap reads from.

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("plot_rater_agreement_heatmap", run.dontrun = TRUE)
if (FALSE) { # \dontrun{
# Saved synthetic JML/RSM analysis of example_core.
# For your own data, fit a model first; see ?fit_mfrm.
example_fit <- readRDS(system.file("examples", "core-jml.rds", package = "mfrmr"))
fit <- example_fit$fit
p <- plot(fit, type = "agreement", view = "heatmap", draw = FALSE)
dim(plot_data(p, "matrix"))
# Look for (default `metric = "exact"`):
# - Off-diagonal cells close to the corresponding entry of
#   `summary(diag)$interrater$ExactAgreement` indicate consistent
#   pair behaviour; cells well below the average mark a pair
#   that disagrees more than the rest.
# - With `metric = "correlation"` the colour scale switches to
#   `[-1, 1]`; positive cells = pairs agree on relative ordering,
#   negative cells = pairs systematically rank persons in opposite
#   directions. Review context, exposure and sample size before deciding
#   whether any rater needs follow-up.
} # }