IRTC
1.1.1Marginal Maximum Likelihood Estimation for Item Response Models
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-07-256 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 88%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 5%
Downloads
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Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
1 release. R releases are shown for context.
- 1.1.1Latest2026-07-24 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-24
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 15 KB / 3 files
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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Run in R for the authors' preferred citation:
citation("IRTC")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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