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IRTC

Marginal Maximum Likelihood Estimation for Item Response Models

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>.

Versions across snapshots

VersionRepositoryFileSize
1.1.1 rolling linux/jammy R-4.5 IRTC_1.1.1.tar.gz 723.0 KiB
1.1.1 rolling linux/noble R-4.5 IRTC_1.1.1.tar.gz 724.7 KiB
1.1.1 rolling source/ R- IRTC_1.1.1.tar.gz 219.8 KiB
1.1.1 latest linux/jammy R-4.5 IRTC_1.1.1.tar.gz 723.0 KiB
1.1.1 latest linux/noble R-4.5 IRTC_1.1.1.tar.gz 724.7 KiB
1.1.1 latest source/ R- IRTC_1.1.1.tar.gz 219.8 KiB
1.1.1 2026-04-23 source/ R- IRTC_1.1.1.tar.gz 0 B

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