plot_scores: Scatter Plot for True vs Estimated Scores, True Score vs...

In autoFC: Automatic Toolkit for Construction, Optimization, Scoring and Simulation of Forced-Choice Tests

Scatter Plot for True vs Estimated Scores, True Score vs Absolute Error, etc.

Description

This function provides a simple, enhanced diagnostic plot examining the performance of the forced-choice scale based on simulated or known true scores.

Usage

plot_scores(x_scores, y_scores, type = c("simple", "abs.diff"), ...)

Arguments

x_scores	Numeric vector. Scores to be plotted on the x-axis (typically True Scores).
y_scores	Numeric vector. Scores to be plotted on the y-axis (typically Estimated Scores).
type	Character. Which type of plot to display? Options are "simple" for an x-y scatter plot, or "abs.diff" for plotting the absolute difference abs(y - x) against x. Defaults to "simple".
...	Additional graphical parameters passed to plot() (e.g., main, pch).

Details

This function extends base R plot() by automatically adding standard diagnostic reference lines (a 1:1 identity line for "simple", and a 0-error baseline for "abs.diff") to aid visual inspection of bias.

Value

A base R scatter plot.

Examples

true <- rnorm(100)
est <- true + rnorm(100, 0, 0.3)
plot_scores(true, est, type = "simple", main = "Recovery")
plot_scores(true, est, type = "abs.diff", main = "Error Magnitude")

autoFC documentation built on July 14, 2026, 5:07 p.m.