View source: R/api-plotting-secondary.R
| plot_local_dependence_heatmap | R Documentation |
Builds an N x N heatmap of pairwise standardized residuals between facet levels, computed from the diagnostics observation table. Cells with large absolute values flag pairs of facet elements (e.g. two raters, two items) whose residuals co-move more than the main-effects MFRM expects, which is the standard Yen Q3-style indicator of local response dependence.
plot_local_dependence_heatmap(
fit,
diagnostics = NULL,
facet = "Rater",
min_pairs = 5L,
preset = c("standard", "publication", "compact", "monochrome"),
draw = TRUE
)
fit |
An |
diagnostics |
Optional |
facet |
Facet whose levels are placed on both axes (default
|
min_pairs |
Minimum number of shared response opportunities
required to retain a pair. Pairs below the threshold are shown
as |
preset |
Visual preset. |
draw |
If |
This helper complements plot_marginal_pairwise(): the marginal
version uses posterior-integrated agreement residuals on a
top-N pair list, while this view shows every pair on a shared color
scale so an analyst can scan for diagonal blocks or hotspots.
An mfrm_plot_data whose data slot bundles the symmetric
residual matrix, the long-form pairs table, and the threshold
used.
plot_marginal_pairwise(), plot_qc_dashboard(),
mfrmr_visual_diagnostics
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
method = "JML", maxit = 30)
p <- plot_local_dependence_heatmap(fit, draw = FALSE)
dim(p$data$matrix)
# Look for: |off-diagonal correlation| < 0.2 is the typical
# acceptable regime; values >= 0.3 (Yen 1984 / Marais 2013
# guideline) flag pairs that may share dependence beyond the
# main-effects MFRM. Inspect those cells in `diag$obs`.
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