Package: ohoegdm 0.1.0
James Joseph Balamuta
ohoegdm: Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data
Perform a Bayesian estimation of the ordinal exploratory Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data described by Culpepper, S. A. and Balamuta, J. J. (In Press) <doi:10.1080/00273171.2021.1985949>.
Authors:
ohoegdm_0.1.0.tar.gz
ohoegdm_0.1.0.zip(r-4.5)ohoegdm_0.1.0.zip(r-4.4)ohoegdm_0.1.0.zip(r-4.3)
ohoegdm_0.1.0.tgz(r-4.4-x86_64)ohoegdm_0.1.0.tgz(r-4.4-arm64)ohoegdm_0.1.0.tgz(r-4.3-x86_64)ohoegdm_0.1.0.tgz(r-4.3-arm64)
ohoegdm_0.1.0.tar.gz(r-4.5-noble)ohoegdm_0.1.0.tar.gz(r-4.4-noble)
ohoegdm_0.1.0.tgz(r-4.4-emscripten)ohoegdm_0.1.0.tgz(r-4.3-emscripten)
ohoegdm.pdf |ohoegdm.html✨
ohoegdm/json (API)
NEWS
| # Install 'ohoegdm' in R: |
| install.packages('ohoegdm', repos = c('https://tmsalab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tmsalab/ohoegdm/issues
diagnostic-modelexploratory-diagnostic-modelspsychometrics
Last updated 3 years agofrom:3c8b91ca54. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 01 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 01 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 01 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 01 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 01 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 01 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 01 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 01 2024 |
Exports:gen_bijectionvectorGenerateAtableohoegdmsim_slcm
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate a vector to map polytomous vector to integers | gen_bijectionvector |
| Generate tables that store different design elements | GenerateAtable |
| Ordinal Higher-Order General Diagnostic Model under the Exploratory Framework (OHOEGDM) | ohoegdm |
| Simulate Ordinal Item Data from a Sparse Latent Class Model | sim_slcm |
