irtc_ctt: Classical Test Theory Item Statistics

In IRTC: Marginal Maximum Likelihood Estimation for Item Response Models

Classical Test Theory Item Statistics

Description

Computes classical item statistics: item means and difficulty (share of the maximum score), corrected item-total (item-rest) correlations, Cronbach's alpha and alpha-if-item-deleted.

Usage

irtc_ctt(x, key = NULL)

## S3 method for class 'irtc_ctt'
print(x, lang = irtc_lang(), ...)

Arguments

x	An irtc_data object, a data frame, a matrix, or a fitted irtc model (its stored response data are used). For the print method: an irtc_ctt object.
key	An optional answer key; raw responses are scored first via irtc_score.
lang	Output language, "zh" or "en".
...	Ignored.

Value

An object of class irtc_ctt: a list with items (data frame with columns item, N, miss_rate, max_score, M, pvalue, discr, alpha_if_deleted), alpha, n_persons and n_items.

See Also

irtc_quality, irtc_itemfit

Examples

set.seed(1)
theta <- rnorm(200)
resp <- as.data.frame(sapply(seq(-1, 1, length.out = 6), function(b) {
    as.numeric(runif(200) < plogis(theta - b))
}))
ctt <- irtc_ctt(resp)
ctt$alpha
ctt$items

IRTC documentation built on July 24, 2026, 5:07 p.m.