plot_item_curves: Plot Item Characteristic Curves (ICC)

In GLMBasedRaschEstimation: GLM-Based Estimation for Rasch Model Parameters

Plot Item Characteristic Curves (ICC)

Description

Plot Item Characteristic Curves (ICC)

Usage

plot_item_curves(theta_all, Modified_prob_matrix, results)

Arguments

theta_all	A numeric vector of ability levels.
Modified_prob_matrix	The matrix returned by compute_Modified_probabilities.
results	The data frame returned by fit_binary_irt.

Value

No return value, called for side effects. It generates a series of plots showing the Item Characteristic Curves (ICC) for each item in the model.

Examples

set.seed(123)
sample_data <- matrix(sample(c(0, 1), 100, replace = TRUE), ncol = 10)
prepared <- prepare_data(sample_data)
irt_results <- fit_binary_irt(prepared$matrix, prepared$total_score)

theta_range <- seq(0, 10, length.out = 100)
probs <- compute_Modified_probabilities(irt_results, theta_range)

# Plot the curves
plot_item_curves(theta_range, probs, irt_results)

GLMBasedRaschEstimation documentation built on April 22, 2026, 9:08 a.m.