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IRTM: Theory-Driven Item Response Theory (IRT) Models
IRT-M is a semi-supervised approach based on Bayesian Item Response Theory that produces theoretically identified underlying dimensions from input data and a constraints matrix. The methodology is fully described in 'Morucci et al. (2024), "Measurement That Matches Theory: Theory-Driven Identification in Item Response Theory Models"'. Details are available at <https://www.cambridge.org/core/journals/american-political-science-review/article/measurement-that-matches-theory-theorydriven-identification-in-item-response-theory-models/395DA1DFE3DCD7B866DC053D7554A30B>.
Getting started
Browse package contents
Package details |
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| Author | Marco Morucci [aut], Margaret Foster [cre] (<https://orcid.org/0000-0002-6418-8394>), David Siegel [aut] (<https://orcid.org/0000-0003-1619-6119>) |
| Maintainer | Margaret Foster <m.jenkins.foster@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.0.1.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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