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IRTC  

Marginal Maximum Likelihood Estimation for Item Response Models
View on CRAN: Click here


Download and install IRTC package within the R console
Install from CRAN:
install.packages("IRTC")

Install from Github:
library("remotes")
install_github("cran/IRTC")

Install by package version:
library("remotes")
install_version("IRTC", "1.1.1")



Attach the package and use:
library("IRTC")
Maintained by
Kunxiang Ma
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-24
Latest Update: 2026-07-24
Description:
Self-contained marginal maximum likelihood (MML) estimation for unidimensional and multidimensional item response models, including the Rasch / one-parameter logistic, partial credit, rating scale, two-parameter logistic and generalised partial credit models, with latent regression, multiple groups and case weights. A parallelised, dimension-factorised streaming estimation engine supports large between-item (simple-structure) multidimensional models with bounded memory and an opt-in controlled-accuracy quadrature mode that reports a measured approximation error. A usability layer serves non-specialists and automated pipelines: one-stop estimation from common file formats ('Excel', delimited text, 'SPSS', 'Stata', 'SAS') with automatic cleaning and answer-key scoring, pre-estimation data checks, classical item statistics and item fit, plain-language quality ratings, bilingual (English/Chinese) output, spreadsheet exports for item banking and cross-year linking, audience-specific 'Word'/'HTML' reports, and machine-readable results with structured error conditions. Methods follow Adams, Wilson and Wang (1997) <doi:10.1177/0146621697211001>.
How to cite:
Kunxiang Ma (2026). IRTC: Marginal Maximum Likelihood Estimation for Item Response Models. R package version 1.1.1, https://cran.r-project.org/web/packages/IRTC. Accessed 20 Sep. 2026.
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