IRTC-package: Marginal Maximum Likelihood Estimation for Item Response...

In IRTC: Marginal Maximum Likelihood Estimation for Item Response Models

Marginal Maximum Likelihood Estimation for Item Response Models

Description

A self-contained marginal maximum likelihood estimation package for unidimensional and multidimensional item response models. It supports Rasch / 1PL, partial credit, rating scale, 2PL and generalized partial credit models, latent regression, multiple groups, case weights, and a bounded-memory streaming engine for large simple-structure models.

Details

Two entry points are provided.

For statisticians, the expert functions irtc.mml and irtc.mml.2pl return an object of class irtc with summary, print, logLik, anova and plot methods.

For non-specialists and automated pipelines, the one-stop function irtc reads data from common file formats (irtc_read), scores raw responses (irtc_score), checks the data (irtc_check_data) and enriches the fitted model with classical statistics (irtc_ctt), item fit (irtc_itemfit) and plain-language quality ratings (irtc_quality). Results can be exported as three Excel workbooks (irtc_excel), audience-specific Word/HTML reports (irtc_report), a layered text summary (plain_summary) or machine-readable structures (irtc_results, irtc_json; schema reference in inst/llms.txt). User-facing output is bilingual; see irtc_lang.

Author(s)

Kunxiang Ma and WEIAN DATA TECH (Beijing) Co., Ltd.

See Also

irtc, irtc.mml, irtc.mml.2pl

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