hIRT
0.3.0Hierarchical Item Response Theory Models
Overview
Implementation of a class of hierarchical item response theory (IRT) models where both the mean and the variance of latent preferences (ability parameters) may depend on observed covariates. The current implementation includes both the two-parameter latent trait model for binary data and the graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) algorithm. Asymptotic standard errors are derived from the observed information matrix.
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- Documented parameters
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- Return-value docs
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- References docs
- 22%
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Code & Tests
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People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2026-01-30requires archived package 'pryr'
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.3.02020-03-26 · diff ↗
- 0.2.02019-06-13 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 0.1.32018-09-16 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 0.1.22017-08-01 · diff ↗
- 0.1.12017-07-24 · diff ↗
- 0.1.02017-07-23
Show 1 earlier events
- RR 3.4.0 released · 2017-04-21
Package metadata
- Total releases
- 6
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.4.0
- Bundled data
- 7.4 KB / 1 file
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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Run in R for the authors' preferred citation:
citation("hIRT")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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