Plot prespecified D-study plans and their differences

Show G/Phi or SEM for every plan, including the reference. Use view = "differences" for changes from the reference with approximate pointwise intervals. In that view, the vertical zero line represents no change; an interval crossing it does not establish equivalence. Positive G/Phi differences or negative SEM differences favor the comparison plan. The method requires normal random effects.

Usage

# S3 method for class 'mfrm_multivariate_d_comparison'
plot(
  x,
  type = c("coefficients", "sem"),
  draw = TRUE,
  preset = "standard",
  view = c("plans", "differences"),
  ...
)

Arguments

x

A result from mfrm_multivariate_d_compare().

type

"coefficients" for G/Phi or "sem" for SEM.

draw

Draw the figure; FALSE returns its data only.

preset

Plot style: "standard", "publication", "compact", or "monochrome".

view

"plans" (default) shows point projections on their original scale, with a diamond for the reference. "differences" shows paired changes and their approximate intervals.

...

Reserved; additional arguments are rejected.

Value

Invisibly, an mfrm_plot_data object. plot_data() extracts the exact comparison table, point-projection series (including the reference), unavailable rows for the selected view, interval_unavailable rows, design_grid, reference, weights, title and labels. Base graphics are supported; automatic ggplot conversion is not provided for this plot.

Details

The plan view connects supplied plans in their original row order. Both facet counts appear on the horizontal axis; lines are visual guides, not an interpolated response to changing one count. For conventional D-study curves that vary one count while holding the other constant, use plot.mfrm_multivariate_d_study(). The plan view has no sampling intervals: adding the reference estimate to a difference interval would not produce a confidence interval for the individual plan.

Plans and score weights must have been specified before inspecting the results. In the difference view, intervals are not simultaneous over plans or metrics. A point without an interval is retained as an open circle; an asterisk marks rows with unavailable intervals. Missing values are never replaced by zero. Each difference panel has its own horizontal scale. Original score units apply to SEM differences. The figure identifies the score/composite, its weights and the reference counts. All plotted plans are future complete crossed plans, even when the source design is incomplete.

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_multivariate_d_compare()