Summary plot of differential functioning effect sizes

Compact effect-size summary for a analyze_dff() / analyze_dif() result. Shows each contrast's signed effect size as a horizontal bar with a vertical reference at zero, coloured by the method-appropriate classification. Current residual and refit screening labels use the neutral colour; refit output does not receive ETS A/B/C labels.

Usage

plot_dif_summary(
  x,
  top_n = 30L,
  sort_by = c("abs_effect", "effect", "classification"),
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE,
  ci_level = NULL,
  effect_thresholds = NULL,
  effect_axis_label = NULL
)

Arguments

x: Output from analyze_dff() or analyze_dif().
top_n: Maximum rows shown (default 30).
sort_by: "abs_effect" (default), "effect", or "classification".
preset: Visual preset.
draw: If TRUE, draw with base graphics.
ci_level: Optional confidence level for approximate normal intervals drawn from Effect +/- z * SE when finite standard errors are available. Use NULL (default) to omit intervals.
effect_thresholds: Optional numeric vector of absolute effect-size guide lines to draw at +/- threshold. These are display aids, not ETS classification boundaries.
effect_axis_label: Optional x-axis label override. When NULL, the label is chosen from the DFF method.

Value

An mfrm_plot_data object whose data slot contains columns Pair, Effect, SE, Classification, Color.

Interpreting output

Bars are anchored at zero. Width corresponds to effect size on the contrast's native scale. For method = "residual", this is the observed-minus-expected average screening contrast between groups. For method = "refit", this is the subgroup parameter difference on the fitted logit scale when linking support allows a comparable contrast. Current DFF/DIF classifications are screening-only, so bars use the preset's neutral colour.

Examples

# \donttest{
toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "JML", maxit = 30)
#> Warning: Optimization convergence review did not produce an inference-ready numerical solution (code = 1, status = iteration_limit). Optimizer reached the iteration limit before the terminal gradient became small enough for review-only acceptance. Inspect the model specification, data support, and starting values. Do not interpret estimates until the review is resolved.
diag <- diagnose_mfrm(fit, residual_pca = "none")
dff <- analyze_dff(fit, diagnostics = diag,
                   facet = "Rater", group = "Group", data = toy)
unique(dff$dif_table$ClassificationSystem)
#> [1] "screening"
p <- plot_dif_summary(dff, draw = FALSE)
head(p$data$data)
#>          Pair      Effect        SE CI_Lower CI_Upper  Classification
#> 1 R01 | A | B  0.16851952 0.1369979       NA       NA Screen negative
#> 2 R02 | A | B -0.13201751 0.1419285       NA       NA Screen negative
#> 3 R03 | A | B -0.11255952 0.1377812       NA       NA Screen negative
#> 4 R04 | A | B  0.07636974 0.1412431       NA       NA Screen negative
#>   ClassificationSystem   Color
#> 1            screening #6b7280
#> 2            screening #6b7280
#> 3            screening #6b7280
#> 4            screening #6b7280
# }