Plot saved latent-population coefficients or contrasts

Read point estimates and their experimental pointwise intervals from an existing population analysis, without fitting or recalculating uncertainty.

Usage

# S3 method for class 'mfrm_population_intervals'
plot(
  x,
  type = c("coefficients", "contrasts"),
  draw = TRUE,
  preset = "standard",
  reference = 0,
  ...
)

Arguments

x

A saved result from mfrm_population_intervals().

type

Show "coefficients" (default, including the intercept) or the prespecified "contrasts" stored in x. Residual variance has different units and remains in summary(x) rather than sharing this axis.

draw

Logical; FALSE returns the plot data without drawing.

preset

A package plot preset, including "publication" and "monochrome". The session default is used when omitted.

reference

Optional finite vertical reference, default zero; NULL omits it. This is not a practical-importance or automatic decision threshold.

...

Unused; unsupported arguments are rejected.

Value

Invisibly, an mfrm_plot_data object. table preserves selected source rows and adds PlotStatus, Label and Y; intervals retains the complete original table. population_spec preserves the formula, trained terms, factor levels and coding; population_coding is a readable coding table. contrast_weights, source identity, settings, numerical checks and interpretation notes accompany the figure. Use plot_data() to inspect these and as_ggplot() for an editable figure with the same saved values.

Details

Rows retain their saved order. Filled circles and lines show numerically available intervals. Crosses with a CI unavailable label retain finite points without eligible finite bounds. A missing point keeps its labeled row without a marker; it is never plotted at zero. Titles and explanatory notes are returned, not drawn. No significance colors or automatic classifications are added. Plotting does not requalify a saved numerical result.

Coefficients describe the conditional population mean on the fitted native ability scale. A continuous coefficient is per unit of its fitted predictor; the intercept depends on predictor zero values and factor coding. Read interactions, transformations and categorical comparisons using the saved coding, not an assumed reference group. Coefficients on different predictor scales are not directly comparable measures of importance. Higher ability predicts higher coded ratings in these RSM/PCM models; whether that is better performance depends on the rubric. Coefficients are not standardized effects.

Contrasts use the stored linear weights and may describe a conditional mean or a difference between means. They are not individual ability differences, causal effects, simultaneous intervals or prediction intervals. Numerical availability does not establish nominal coverage: the source's experimental status, failed checks and qualifications remain in notes and the tables. A wide interval remains visible. Missing bounds are not infinite endpoints. When source-anchor uncertainty was requested, the saved intervals include that contribution. The returned subtitle, settings and anchor_uncertainty distinguish it from intervals conditional on exact supplied anchors; conditional bounds remain in the returned table.

For an executable bundled-data example, run the example on mfrm_population_intervals(), which creates ci and both views. Then use p <- plot(ci, type = "contrasts", draw = FALSE), plot_data(p, "contrast_weights") and plot_data(p, "notes") to read it. as_ggplot(ci, type = "contrasts") converts the same saved result.

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

mfrm_population_intervals(), mfrmr_interval_guide(), plot.mfrm_facet_intervals()