Provides Bayesian estimation of Item Response Theory models that decompose item difficulty into cognitive operations or rules. Implements the Linear Logistic Test Model (LLTM; Fischer (1973) <doi:10.1016/0001-6918(73)90003-6>), the Multicomponent Latent Trait Model for Diagnosis (MLTM-D; Embretson and Yang (2013) <doi:10.1007/s11336-012-9296-y>), and the Generalized Multicomponent Latent Trait Model for Diagnosis (GMLTM-D; Ramirez et al. (2024) <doi:10.3390/jintelligence12070067>). All models are estimated via Hamiltonian Monte Carlo using 'Stan' through the 'rstan' interface. Includes tools for model validation, reliability estimation, and visualization of item characteristic curves. Supports user-defined prior distributions for all model parameters.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | rstan (≥ 2.21.0), ggplot2, gridExtra, grid, utils, parallel, loo, RColorBrewer |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2026-06-30 |
| DOI: | 10.32614/CRAN.package.GMLTM (may not be active yet) |
| Author: | Eduar Ramirez [aut, cre], Marcos Jimenez [aut], Vithor R. Franco [aut], Jesus Alvarado [aut] |
| Maintainer: | Eduar Ramirez <edrami02 at ucm.es> |
| BugReports: | https://github.com/Eduar-Ramirez/GMLTM-D/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/Eduar-Ramirez/GMLTM-D |
| NeedsCompilation: | no |
| SystemRequirements: | C++17, GNU make |
| Language: | en-US |
| Materials: | README, NEWS |
| CRAN checks: | GMLTM results |
| Reference manual: | GMLTM.html , GMLTM.pdf |
| Vignettes: |
Introduction to GMLTM (source, R code) |
| Package source: | GMLTM_0.1.0.tar.gz |
| Windows binaries: | r-devel: GMLTM_0.1.0.zip, r-release: not available, r-oldrel: GMLTM_0.1.0.zip |
| macOS binaries: | r-release (arm64): GMLTM_0.1.0.tgz, r-oldrel (arm64): GMLTM_0.1.0.tgz, r-release (x86_64): GMLTM_0.1.0.tgz, r-oldrel (x86_64): GMLTM_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=GMLTM to link to this page.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.