Package: IRTM 0.0.1.2

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>.

Authors:Marco Morucci [aut], Margaret Foster [aut], David Siegel [aut, cre]

IRTM_0.0.1.2.tar.gz
IRTM_0.0.1.2.zip(r-4.7)IRTM_0.0.1.2.zip(r-4.6)IRTM_0.0.1.2.zip(r-4.5)
IRTM_0.0.1.2.tgz(r-4.6-x86_64)IRTM_0.0.1.2.tgz(r-4.6-arm64)IRTM_0.0.1.2.tgz(r-4.5-x86_64)IRTM_0.0.1.2.tgz(r-4.5-arm64)
IRTM_0.0.1.2.tar.gz(r-4.7-arm64)IRTM_0.0.1.2.tar.gz(r-4.7-x86_64)IRTM_0.0.1.2.tar.gz(r-4.6-arm64)IRTM_0.0.1.2.tar.gz(r-4.6-x86_64)
IRTM_0.0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
IRTM/json (API)
NEWS

# Install 'IRTM' in R:
install.packages('IRTM', repos = c('https://dasiegel.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • MCodes - Methodological Codes
  • synth_idvs - Synthetic Independent Variables
  • synth_questions - Questions for the Synthetic European sentiment survey in the vignette

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

3.16 score 29 scripts 526 downloads 11 exports 43 dependencies

Last updated from:a955988604. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK199
linux-devel-x86_64OK221
source / vignettesOK364
linux-release-arm64OK206
linux-release-x86_64OK216
macos-release-arm64OK206
macos-release-x86_64OK346
macos-oldrel-arm64OK212
macos-oldrel-x86_64OK518
windows-develOK186
windows-releaseOK189
windows-oldrelOK174
wasm-releaseOK140

Exports:dim_corrget_lambdasGeweke_convergenceirt_mirt_visM_constrained_irtmsepair_gen_anchorsstandardize_thetatheta_avtheta_lambda_traceplots

Dependencies:clicodacpp11dplyrfarvergenericsggplot2ggridgesgluegmmgtableisobandlabelinglatticelifecyclemagrittrMatrixmvtnormpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppDistRcppProgressreshape2rlangS7sandwichscalesstringistringrtibbletidyselecttmvtnormtruncnormutf8vctrsviridisLitewithrzoo

IRT-M Vignette (Synthetic Data)

Margaret J Foster

Rendered fromintroduction_synth.Rmdusingknitr::rmarkdownon May 22 2026.

Last update: 2026-04-21
Started: 2025-04-19