simCAT_MX: Simulated Mixed-Item Format CAT Data

In irtQ: Unidimensional Item Response Theory Modeling

Simulated Mixed-Item Format CAT Data

Description

A simulated dataset for computerized adaptive testing (CAT), containing an item pool, sparse response data, and examinee ability estimates. The item pool includes both dichotomous and polytomous items.

Usage

simCAT_MX

Format

A list of length three:

item.prm

A data frame in item metadata format consisting of 200 dichotomous items and 30 polytomous items.

• Dichotomous items: Calibrated using the IRT 2PL model.

• Polytomous items: Calibrated using the Generalized Partial Credit Model (GPCM), with four score categories (0, 1, 2, 3).

res.dat

A matrix of item responses from 30,000 examinees (rows) to 230 items (columns). NA marks an item that was not administered to the examinee. The columns are named Item.dc.1 to Item.dc.200 and Item.py.1 to Item.py.30, not by the id column of item.prm (V1 to V230); the columns follow the row order of item.prm.

score

A numeric vector of ability estimates for the 30,000 examinees.

Author(s)

Hwanggyu Lim [e-mail]

Examples

# structure of the data
str(simCAT_MX, max.level = 1)


# item fit of three dichotomous items and two polytomous items
loc <- c(1:3, 201:202)
x <- simCAT_MX$item.prm[loc, ]
data <- simCAT_MX$res.dat[, loc]
irtfit(
  x = x, score = simCAT_MX$score, data = data, group.method = "equal.freq",
  n.width = 10, loc.theta = "average", range.score = c(-4, 4), D = 1
)

irtQ documentation built on Oct. 5, 2026, 5:08 p.m.