plot_anova: Plot Sequential ANOVA Results

In sprtt: Sequential Probability Ratio Tests Toolbox

Plot Sequential ANOVA Results

Description

Creates a visualization of the sequential probability ratio test (SPRT) for ANOVA results, showing the log-likelihood ratio trajectory across sample sizes and decision boundaries.

Usage

plot_anova(
  anova_results,
  labels = TRUE,
  position_labels_x = 0.15,
  position_labels_y = 0.1,
  position_lr_x = NULL,
  position_lr_y = NULL,
  font_size = 15,
  line_size = 1,
  highlight_color = "#CD2626"
)

Arguments

anova_results	A seq_anova_results object from seq_anova(). Important: The seq_anova() function must be called with plot = TRUE to generate the necessary data for plotting.
labels	Logical. If TRUE (default), display decision labels ("Accept H0" / "Accept H1") and the likelihood ratio at the decision point.
position_labels_x	Numeric value between 0 and 1 controlling the horizontal position of decision labels as a proportion of maximum sample size. Default is 0.15 (left side); 0.5 centers the labels.
position_labels_y	Numeric value controlling the vertical spacing between decision boundaries and their labels. The value is multiplied by ⁠max(|log-likelihood ratio|)⁠ to determine spacing. Larger values move labels further from boundaries. Default is 0.075.
position_lr_x	Optional numeric value for the x-coordinate (sample size) of the likelihood ratio label. If NULL (default), positioned at the decision point or final sample size.
position_lr_y	Optional numeric value for the y-coordinate (log-likelihood ratio) of the likelihood ratio label. If NULL (default), positioned at y = 0 for early decisions, or slightly offset for continuing sampling scenarios.
font_size	Numeric. Base font size for plot text. Default is 20.
line_size	Numeric. Line width for the trajectory and boundaries. Default is 1.5.
highlight_color	Character string. Color for highlighting the decision point or final sample. Default is "#CD2626" (red).

Value

A ggplot2::ggplot() object showing:

• Log-likelihood ratio trajectory across sample sizes

• Dashed horizontal lines indicating decision boundaries

• Highlighted point showing where decision was reached (or final sample)

• Optional labels for decision regions and likelihood ratio value

Examples

# simulate data for the example ------------------------------------------------
set.seed(3)
data <- sprtt::draw_sample_normal(3, f = 0.25, max_n = 50)

# calculate the SPRT -----------------------------------------------------------
anova_results <- sprtt::seq_anova(y~x, f = 0.25, data = data, plot = TRUE)

# plot the results -------------------------------------------------------------
# default settings
sprtt::plot_anova(anova_results)
# variant 1
sprtt::plot_anova(anova_results,
                 labels = TRUE,
                 position_labels_x = 0.05,
                 position_lr_x = 150,
                 position_lr_y = 0,
                 highlight_color = "green"
                 )
# variant 2
sprtt::plot_anova(anova_results,
                  labels = TRUE,
                  position_labels_x = 0.15,
                  position_labels_y = 0.2,
                  position_lr_x = 60,
                  position_lr_y = 1,
                  font_size = 25,
                  line_size = 2,
                  highlight_color = "darkred"
)
# no labels
sprtt::plot_anova(anova_results,
                 labels = FALSE
                 )
# custom additions
sprtt::plot_anova(anova_results) +
  ggplot2::geom_vline(xintercept = 66, linewidth = 1, linetype = "dashed")

# further information ----------------------------------------------------------
# run this code:
vignette("one_way_anova", package = "sprtt")

sprtt documentation built on May 6, 2026, 5:06 p.m.