extract_rasch_difficulties_ordered: Extract Rasch Item Difficulties in Original Order

In GLMBasedRaschEstimation: GLM-Based Estimation for Rasch Model Parameters

Extract Rasch Item Difficulties in Original Order

Description

Extract Rasch Item Difficulties in Original Order

Usage

extract_rasch_difficulties_ordered(final_logit_matrix)

Arguments

final_logit_matrix

The matrix returned by rasch_logit.

Value

A data frame containing the calculated difficulty parameters for each item, with the following columns:

• Item_Number: The sequential index of the item.

• Item_Name: The name or label of the item.

• Difficulty_Logit: The item difficulty parameter (beta) expressed on the logit scale, rounded to four decimal places. Higher values indicate more difficult items.

Examples

set.seed(123)
sample_data <- matrix(sample(c(0, 1), 100, replace = TRUE), ncol = 10)
colnames(sample_data) <- paste0("Q", 1:10)
prepared <- prepare_data(sample_data)
irt_results <- fit_binary_irt(prepared$matrix, prepared$total_score)
probs <- compute_Modified_probabilities(irt_results, prepared$total_score)
logits <- rasch_logit(probs)

difficulty_table <- extract_rasch_difficulties_ordered(logits)

print(difficulty_table)

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