Normal quantile-quantile plot of person standardized residuals

Produces a Q-Q plot of per-person standardized residuals. Under the fitted Rasch-family model the residuals are approximately N(0, 1), so deviations from the reference line diagnose distributional misfit that mean-square summaries may miss.

Usage

plot_residual_qq(
  fit,
  diagnostics = NULL,
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE
)

Arguments

fit

An mfrm_fit.

diagnostics

Optional diagnose_mfrm() output; required entries are generated internally when absent.

preset

Visual preset.

draw

If TRUE, print the ggplot object.

Value

Invisibly, a ggplot object. plot_data(p, "data") contains Person, Theoretical, Sample columns.

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.

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("plot_residual_qq", 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 = "residual_qq", draw = FALSE)
head(plot_data(p, "data"))
# Look for: points hugging the y = x reference line. Heavy upper-
#   right tails indicate persons whose residual aggregates exceed
#   the standard normal expectation; pair with `plot()`
#   for case-level follow-up. This is an exploratory screen; do
#   not treat tail behaviour as a definitive normality test.
} # }